[2024] [2023] [2022] [2021] [2020] [2019] [2018] [2017] [2016] [2015] [2014]

2024

  • Cong, Y., Xu, M., Simon, C., Chen, S., Ren, J., Xie, Y., Rosenhahn, B., Xiang, T., and He, S. (2024)FLATTEN: optical FLow-guided ATTENtion for consistent text-to-video editing. In International Conference on Learning Representations (ICLR).
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  • Xu, R., Beltran-Gutierrez, R. E., K{ä}ding, M., Lange, A., Marx, S., and Ostermann, J. (2024)Frequency dependent amplitude response of different couplant materials for mounting piezoelectric sensors, NDT \& E International 141.
    BibTeXEndNoteBibSonomy
  • Kluger, F., and Rosenhahn, B. (2024)PARSAC: Accelerating Robust Multi-Model Fitting with Parallel Sample Consensus. In AAAI.
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  • Hinrichs, R. (2024)Kompression der Erregungsmuster von Cochlea-Implantaten, VDI Verlag.
    BibTeXEndNoteBibSonomy
  • Lange, A., Xu, R., K{ä}ding, M., Marx, S., and Ostermann, J. (2024)Matched Filter for Acoustic Emission Monitoring in Noisy Environments: Application to Wire Break Detection (accepted), acoustics, Special Issue: Advances in Industrial and Research Applications of Acoustic Emission Testing.
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  • Cong, Y., Xu, M., Simon, C., Chen, S., Ren, J., Xie, Y., Perez-Rua, J.-M., Rosenhahn, B., Xiang, T., and He, S. (2024)FLATTEN: optical FLow-guided ATTENtion for consistent text-to-video editing. In International Conference on Learning Representations (ICLR).
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  • Wallat, J., Jatowt, A., and Anand, A. (2024)Temporal Blind Spots in Large Language Models, ACM International Conference on Web Search and Data Mining (WSDM) (Proceeding, no out yet, Ed.) 17.
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  • Hinrichs, R., Gerkens, K., Lange, A., and Ostermann, J. (2024)Blind Extraction of Guitar Effects Through Blind System Inversion and Neural Guitar Effect Modeling, EURASIP Journal on Audio, Speech, and Music Processing.
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  • Chen, S., Xu, M., Ren, J., Cong, Y., He, S., Xie, Y., Sinha, A., Luo, P., Xiang, T., and Perez-Rua, J.-M. (2024)GenTron: Delving Deep into Diffusion Transformers for Image and Video Generation. In Proc. of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
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  • Reinders, C., Yang, M. Y., and Rosenhahn, B. (2024)Two Worlds in One Network: Fusing Deep Learning and Random Forests for Classification and Object Detection, Volunteered Geographic Information.
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  • Chen, Y.-H., Gao, Z.-L., Benjak, M., and Peng, W.-H. (2024)Response to Call for Learning-Based Video Codecs for Study of Quality Assessment by NYCU and LUH, 14th Meeting of ISO/IEC JTC 1/SC 29/AG 5 Document m66163.
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2023

  • Ganguly, N., Fazlija, D., Badar, M., Fisichella, M., Sikdar, S., Schrader, J., Wallat, J., Rudra, K., Koubarakis, M., Patro, G. K., Amri, W. Z. E., and Nejdl, W. (2023)A Review of the Role of Causality in Developing Trustworthy AI Systems.
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  • Rohlfing, C., Meyer, T., Schneider, J., and Voges, J. (2023)Python Wrapper for Context-based Adaptive Binary Arithmetic Coding. In 2023 IEEE International Conference on Visual Communications and Image Processing (VCIP).
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  • Basso, L., Ren, Z., and Nejdl, W. (2023)Efficient ECG-Based Atrial Fibrillation Detection via Parameterised Hypercomplex Neural Networks. In 2023 31st European Signal Processing Conference (EUSIPCO), pp. 1375–1379.
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  • Jaradeh, M. Y., Singh, K., Stocker, M., Both, A., and Auer, S. (2023)Information extraction pipelines for knowledge graphs, Knowl. Inf. Syst. 65, 1989–2016.
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  • Kabongo, S., D’Souza, J., and Auer, S. (2023)Zero-Shot Entailment of Leaderboards for Empirical {AI} Research. In {ACM/IEEE} Joint Conference on Digital Libraries, {JCDL} 2023, Santa Fe, NM, USA, June 26-30, 2023, pp. 237–241, {IEEE}.
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  • Chang, Y., Ren, Z., Nguyen, T. T., Qian, K., and Schuller, B. W. (2023)Knowledge transfer for on-device speech emotion recognition with neural structured learning. In ICASSP.
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  • Schier, M., Reinders, C., and Rosenhahn, B. (2023)Learned Fourier Bases for Deep Set Feature Extractors in Automotive Reinforcement Learning. In 2023 IEEE 26th International Conference on Intelligent Transportation Systems (ITSC), p. to appear.
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  • Schubert, F., Benjamins, C., D{ö}hler, S., Rosenhahn, B., and Lindauer, M. (2023)POLTER: Policy Trajectory Ensemble Regularization for Unsupervised Reinforcement Learning, Transactions on Machine Learning Research.
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  • Adhisantoso, Y. G. (2023)Cross-check of Philips’s Response to Core Experiment for Annotation Data Indexing using B-Tree m62224, ISO/IEC JTC 1/SC 29/WG 8.
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  • Rudolph, M., Wehrbein, T., Rosenhahn, B., and Wandt, B. (2023)Asymmetric Student-Teacher Networks for Industrial Anomaly Detection. In Winter Conference on Applications of Computer Vision (WACV).
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  • Roy, S., Ganguly, N., Sural, S., and Rudra, K. (2023)Interpretable Clinical Trial Search using Pubmed Citation Network. In 2023 IEEE International Conference on Digital Health (ICDH), pp. 328–338.
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  • Ren, Z., Nguyen, T. T., Chang, Y., and Schuller, B. W. (2023)Fast yet effective speech emotion recognition with self-distillation. In ICASSP.
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  • Cong, Y., Yi, J., Rosenhahn, B., and Yang, M. (2023)SSGVS: Semantic Scene Graph-to-Video Synthesis. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops.
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  • Hinrichs, R., Bilsky, J., and Ostermann, J. (2023)Vector-Quantized Feedback Recurrent Autoencoders for the Compression of the Stimulation Patterns of Cochlear Implants at Zero Delay. In Proceedings of the 24th International Conference on Digital Signal Processing.
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  • Ehlert, H., Beaulac, E., Wallbaum, M., Gebauer, C., Rumberg, L., Ostermann, J., and L{ü}dtke, U. (2023)Collecting and Annotating Natural Child Speech Data – Challenges and Interdisciplinary Perspectives. In Elektronische Sprachsignalverarbeitung (ESSV), pp. 72–78.
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  • L{ü}dtke, U., Bornman, J., de Wet, F., Heid, U., Ostermann, J., Rumberg, L., der Linde, J. V., and Ehlert, H. (2023)Multidisciplinary Perspectives on Automatic Analysis of Children’s Language Samples: Where Do We Go from Here?, Folia Phoniatrica et Logopaedica 75, 1–12.
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  • Gebauer, C., Rumberg, L., Ehlert, H., L{ü}dtke, U., and Ostermann, J. (2023)Exploiting Diversity of Automatic Transcripts from Distinct Speech Recognition Techniques for Children’s Speech. In Accepted to Interspeech 2023.
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  • Antoniou, G., and Batsakis, S. (2023)Defeasible Reasoning with Large Language Models–Initial Experiments and Future Directions. In Proceedings of the17th International Rule Challenge, RuleML 2023, p. 7687.
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  • Tang, M., Antic, Z., Fardzadeh, P., Schröder, C., Pietzsch, S., Lentes, J., Hofmann, W., von Wolfggersdorff, L., Zimmerman, M., Horstmann, M., Nejdl, W., Cario, G., Stanulla, M., and Bergmann, A. K. (2023)A machine learning based clinical platform for cancer subtyping and data integration in hematological malignancies, Annals of Oncology 34, S550.
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  • Giglou, H. B., D’Souza, J., and Auer, S. (2023)LLMs4OL: Large Language Models for Ontology Learning. In The Semantic Web - {ISWC} 2023 - 22nd International Semantic Web Conference, Athens, Greece, November 6-10, 2023, Proceedings, Part {I} (Payne, T. R., Presutti, V., Qi, G., Poveda{-}Villal{{ó}}n, M., Stoilos, G., Hollink, L., Kaoudi, Z., Cheng, G., and Li, J., Eds.), pp. 408–427, Springer.
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  • Auer, S., Barone, D. A. C., Bartz, C., Cortes, E. G., Jaradeh, M. Y., Karras, O., Koubarakis, M., Mouromtsev, D., Pliukhin, D., Radyush, D., Shilin, I., Stocker, M., and Tsalapati, E. (2023, March)SciQA benchmark: Dataset and {RDF} dump (Version 5), Zenodo.
    URLBibTeXEndNoteBibSonomy
  • Kaiser, T., Reinders, C., and Rosenhahn, B. (2023)Compensation Learning in Semantic Segmentation. In Computer Vision and Pattern Recognition Workshops (CVPRW).
    BibTeXEndNoteBibSonomy
  • Adhisantoso, Y. G., and Voges, J. (2023)Cross-check of M62859 Results on Updated CE Results for Annotation Data Indexing Using B-Tree, ISO/IEC JTC 1/SC 29/WG 8.
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  • Dockhorn, A., Eberhardinger, M., Loiacono, D., Liebana, D. P., and Veltkamp, R. (2023)Pokegen, Human-Game AI Interaction (Dagstuhl Seminar 22251) 12, 39–42.
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  • Awiszus, M., Dockhorn, A., Hoover, A. K., Liapis, A., Lucas, S. M., Eladhari, M. P., Schrum, J., and Volz, V. (2023)Language Models for Procedural Content Generation, Human-Game AI Interaction (Dagstuhl Seminar 22251) 12, 34–37.
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  • Lee, C.-S., Wang, M.-H., Chen, C.-Y., Yang, F.-J., and Dockhorn, A. (2023)Genetic Assessment Agent for High-School Student and Machine Co-Learning Model Construction on Computational Intelligence Experience. In 2023 IEEE Congress on Evolutionary Computation, pp. 1–8.
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  • Nandy, A., Kapadnis, M. N., Goyal, P., and Ganguly, N. (2023)CLMSM: A Multi-Task Learning Framework for Pre-training on Procedural Text. In The 2023 Conference on Empirical Methods in Natural Language Processing.
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  • Poker, Y., von Hardenberg, S., Hofmann, W., Tang, M., Baumann, U., Schwerk, N., Wetzke, M., Lindenthal, V., Auber, B., Schlegelberger, B., Ott, H., von Bismarck, P., Viemann, D., Dressler, F., Klemann, C., and Bergmann, A. K. (2023)Systematic genetic analysis of pediatric patients with autoinflammatory diseases, Frontiers in Genetics, Frontiers Media {SA} 14.
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  • Lange, A., K{ä}ding, M., Xu, R., Marx, S., and Ostermann, J. (2023)Semi-supervised learning for acoustic emission monitoring of tendons in prestressed concrete bridges. In 14th International Workshop on Structural Health Monitoring (IWSHM).
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  • Benjamins, C., Eimer, T., Schubert, F., Mohan, A., D{ö}hler, S., Biedenkapp, A., Rosenhahn, B., Hutter, F., and Lindauer, M. (2023)Contextualize Me - The Case for Context in Reinforcement Learning, Transactions on Machine Learning Research.
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  • Safikhani, P., and Broneske, D. (2023)Enhancing AutoNLP with fine-tuned BERT models: An evaluation of text representation methods for AutoPyTorch., International Conference on Machine Learning Techniques and NLP 13.
    BibTeXEndNoteBibSonomy
  • Wallat, J., Beringer, F., Anand, A., and Anand, A. (2023)Probing BERT for Ranking Abilities. In Advances in Information Retrieval - 45th European Conference on Information Retrieval, {ECIR} 2023, Dublin, Ireland, April 2-6, 2023, Proceedings, Part {II} (Kamps, J., Goeuriot, L., Crestani, F., Maistro, M., Joho, H., Davis, B., Gurrin, C., Kruschwitz, U., and Caputo, A., Eds.), pp. 255–273, Springer.
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  • Roy, S., Wallat, J., Sundaram, S. S., Nejdl, W., and Ganguly, N. (2023)GENEMASK: Fast Pretraining of Gene Sequences to Enable Few-Shot Learning. In Frontiers in Artificial Intelligence and Applications, pp. 2002–2009.
    AbstractBibTeXEndNoteBibSonomy
  • Olson, C., Wagner, L., and Dockhorn, A. (2023)Evolutionary Optimization of Baba Is You Agents. In 2023 IEEE Congress on Evolutionary Computation (CEC), pp. 1–8.
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  • Hachmann, H., and Rosenhahn, B. (2023)Color-aware Deep Temporal Backdrop Duplex Matting System. In MMSys ’23: Proceedings of the 14th ACM Multimedia Systems Conference.
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  • Schier, M., Reinders, C., and Rosenhahn, B. (2023)Deep Reinforcement Learning for Autonomous Driving Using High-Level Heterogeneous Graph Representations. In International Conference on Robotics and Automation (ICRA), p. to appear.
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  • Adhisantoso, Y. G., Voges, J., and Ostermann, J. (2023)PEKORA: High-Performance 3D Genome Reconstruction Using K-th Order Spearman’s Rank Correlation Approximation [Talk]. In ISMB/ECCB 2023.
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  • D’Souza, J., Hrou, M., and Auer, S. (2023)Evaluating Prompt-Based Question Answering for Object Prediction in the Open Research Knowledge Graph. In Database and Expert Systems Applications - 34th International Conference, {DEXA} 2023, Penang, Malaysia, August 28-30, 2023, Proceedings, Part {I} (Strauss, C., Amagasa, T., Kotsis, G., Tjoa, A. M., and Khalil, I., Eds.), pp. 508–515, Springer.
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  • Hussein, H., Farfar, K. E., Oelen, A., Karras, O., and Auer, S. (2023)Increasing Reproducibility in Science by Interlinking Semantic Artifact Descriptions in a Knowledge Graph. In Leveraging Generative Intelligence in Digital Libraries: Towards Human-Machine Collaboration - 25th International Conference on Asia-Pacific Digital Libraries, {ICADL} 2023, Taipei, Taiwan, December 4-7, 2023, Proceedings, Part {II} (Goh, D. H.- }Lian, Chen, S.- }Jiun, and Tuarob, S., Eds.), pp. 220–229, Springer.
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  • Gebauer, C., Rumberg, L., and Ostermann, J. (2023)Pronunciation Modeling for Children’s Speech. In Elektronische Sprachsignalverarbeitung (ESSV), pp. 79–86.
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  • Roy, S., Wallat, J., Sundaram, S. S., Nejdl, W., and Ganguly, N. (2023)GeneMask: Fast Pretraining of Gene Sequences to Enable Few-Shot Learning, CoRR abs/2307.15933.
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  • Rabby, G., D’Souza, J., Oelen, A., Dvorackova, L., Sv{{á}}tek, V., and Auer, S. (2023)Impact of {COVID-19} research: a study on predicting influential scholarly documents using machine learning and a domain-independent knowledge graph, J. Biomed. Semant. 14, 18.
    URLBibTeXEndNoteBibSonomy
  • Kuhnke, F. (2023)Unsupervised Domain Adaptation for Real-World Head Pose Estimation from Synthetic Data 144.
    BibTeXEndNoteBibSonomy
  • Cong, Y., Yang, M., and Rosenhahn, B. (2023)RelTR: Relation Transformer for Scene Graph Generation, IEEE transactions on pattern analysis and machine intelligence (TPAMI).
    BibTeXEndNoteBibSonomy
  • Xie, H.-S., Chen, Y.-H., Peng, W.-H., Benjak, M., and Ostermann, J. (2023)Rate Adaptation for Learned Two-layer B-frame Coding without Signaling Motion Information. In IEEE International Conference on Visual Communications and Image Processing (VCIP).
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  • Hachmann, H., and Rosenhahn, B. (2023)Human Spine Motion Capture using Perforated Kinesiology Tape. In Computer Vision and Pattern Recognition Workshops (CVPRW).
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  • Papadakis, E., Baryannis, G., Batsakis, S., Adamou, M., Huang, Z., and Antoniou, G. (2023)ADHD-KG: A Knowledge Graph of Attention Deficit Hyperactivity Disorder, Health Information Science and Systems.
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  • M{ü}ntefering, F., Ostermann, J., and Voges, J. (2023)BACON: Bacterial Clone Recognition from Metagenomic Sequencing Data, AICPM 2023.
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  • Brockmann*, J. T., Rudolph*, M., Rosenhahn, B., Wandt, B., and equal contribution), (*. (2023)The voraus-AD Dataset for Anomaly Detection in Robot Applications, Transactions on Robotics.
    BibTeXEndNoteBibSonomy
  • Rosenhahn, B. (2023)Optimization of Sparsity-Constrained Neural Networks as a Mixed Integer Linear Program, Journal of Optimization Theory and Applications 1–24.
    BibTeXEndNoteBibSonomy
  • Rosenhahn, B., and Osborne, T. (2023)Monte Carlo Graph Search for Quantum Circuit Optimization (Accepted), Physical Review A.
    BibTeXEndNoteBibSonomy
  • Xu, L., Dockhorn, A., and Perez-Liebana, D. (2023)Elastic Monte Carlo Tree Search, IEEE Transactions on Games.
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  • Xiao, J., Basso, L., Nejdl, W., Ganguly, N., and Sikdar, S. (2023)IVP-VAE: Modeling EHR Time Series with Initial Value Problem Solvers, arXiv preprint arXiv:2305.06741.
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  • Benjak, M., Chen, Y.-H., Peng, W.-H., and Ostermann, J. (2023)Learning-Based Scalable Video Coding with Spatial and Temporal Prediction. In IEEE International Conference on Visual Communications and Image Processing (VCIP).
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  • Fathalla, S., Lange, C., and Auer, S. (2023)An Upper Ontology for Modern Science Branches and Related Entities. In The Semantic Web - 20th International Conference, {ESWC} 2023, Hersonissos, Crete, Greece, May 28 - June 1, 2023, Proceedings (Pesquita, C., Jim{{é}}nez{-}Ruiz, E., McCusker, J. P., Faria, D., Dragoni, M., Dimou, A., Troncy, R., and Hertling, S., Eds.), pp. 436–453, Springer.
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  • Ekaputra, F. J., Llugiqi, M., Sabou, M., Ekelhart, A., Paulheim, H., Breit, A., Revenko, A., Waltersdorfer, L., Farfar, K. E., and Auer, S. (2023)Describing and Organizing Semantic Web and Machine Learning Systems in the SWeMLS-KG. In The Semantic Web - 20th International Conference, {ESWC} 2023, Hersonissos, Crete, Greece, May 28 - June 1, 2023, Proceedings (Pesquita, C., Jim{{é}}nez{-}Ruiz, E., McCusker, J. P., Faria, D., Dragoni, M., Dimou, A., Troncy, R., and Hertling, S., Eds.), pp. 372–389, Springer.
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  • W{ö}rz, N., Woiwode, D., Sondheim, J., Behrens, D., Rudy, D., and Gl{ü}cksklee, T. (2023)Pflanzenforschung an Bord der ISS, BIOspektrum 29 29, 557.
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  • D’Souza, J., Mulang’, I. O., and Auer, S. (2023)Ranking facts for explaining answers to elementary science questions, Nat. Lang. Eng. 29, 228–253.
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  • Rumberg, L., Gebauer, C., Ehlert, H., Wallbaum, M., L{ü}dtke, U., and Ostermann, J. (2023)Uncertainty Estimation for Connectionist Temporal Classification Based Automatic Speech Recognition. In Accepted to Interspeech 2023.
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  • Auer, S., Barone, D. A. C., Bartz, C., Cortes, E. G., Jaradeh, M. Y., Karras, O., Koubarakis, M., Mouromtsev, D., Pliukhin, D., Radyush, D., Shilin, I., Stocker, M., and Tsalapati, E. (2023, March)SciQA benchmark: Dataset and {RDF} dump (Version 1.0.1), Zenodo.
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  • Liapis, A., Awiszus, M., Champandard, A. J., Cook, M., Denisova, A., Dockhorn, A., Thompson, T., and Zhu, J. (2023)Artificial Intelligence for Audiences, Human-Game AI Interaction (Dagstuhl Seminar 22251) 12, 50–54.
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  • Cook, M., Awiszus, M., Cakmak, D., Denisova, A., Dockhorn, A., Harteveld, C., Liapis, A., Eladhari, M. P., Liebana, D. P., Rombout, L., and Thompson, T. (2023)AI for Romantic Comedies, Human-Game AI Interaction (Dagstuhl Seminar 22251) 12, 37–39.
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  • Avetisyan, H., Safikhani, P., and Broneske, D. (2023)Laughing Out Loud – Exploring AI-Generated and Human-Generated Humor, International Conference on Soft Computing, Artificial Intelligence and Applications (SCAI 2023).
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  • Hinrichs, R., Sitcheu, A. J. Y., and Ostermann, J. (2023)Continuous Sign-Language Recognition using Transformers and Augmented Pose Estimation. In Proceedings of the International Conference on Pattern Recognition Applications and Methods.
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  • Adhisantoso, Y. G., Voges, J., Rohlfing, C., Tunev, V., Ohm, J.-R., and Ostermann, J. (2023)GVC: Efficient Random Access Compression for Gene Sequence Variations. In BMC Bioinformatics, p. 13.
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  • Wehrbein, T., Rosenhahn, B., Matthews, I., and Stoll, C. (2023)Personalized 3D Human Pose and Shape Refinement. In International Conference on Computer Vision Workshops (ICCVW).
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  • Zhu, J., Awiszus, M., Cook, M., Dockhorn, A., Eberhardinger, M., Loiacono, D., Lucas, S. M., Matran-Fernandez, A., Liebana, D. P., Thompson, T., and Veltkamp, R. (2023)Explainable AI for Games, Human-Game AI Interaction (Dagstuhl Seminar 22251) 12, 73–75.
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  • Krause, L. M. K., Manderfeld, E., Gnutt, P., Vogler, L., Wassick, A., Richard, K., Rudolph, M., Hunsucker, K. Z., Swain, G. W., Rosenhahn, B., and Rosenhahn, A. (2023)Semantic Segmentation for Fully Automated Macrofouling Analysis on Coatings after Field Exposure, Biofouling 39, 64–79.
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  • Pestel-Schiller, U., Busch, J., Meinicke, P.-R., and Ostermann, J. (2023)Gain Adapted Quantization in HEVC Coding Applied to Drone Remote Sensing. In 13th Workshop on Hyperspectral Imaging and Signal Processing: Evolution in Remote Sensing (WHISPERS).
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  • Safikhani, P., Avetisyan, H., F{ö}ste-Eggers, D., and Broneske, D. (2023)Automated occupation coding with hierarchical features: A data-centric approach to classification with pre-trained language models., Discover Artificial Intelligence.
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  • Dockhorn, A., and Kruse, R. (2023)State and Action Abstraction for Search and Reinforcement Learning Algorithms, Artificial Intelligence in Control and Decision-making Systems 181–198.
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  • Xu, R., Lange, A., K{ä}ding, M., Marx, S., and Ostermann, J. (2023)Energy spectral analysis of wire breaks in post-tensioned tendons for wind turbines. In 19th EAWE PhD Seminar on Wind Energy, pp. 204–207.
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  • Mohan, A., Benjamins, C., Wienecke, K., Dockhorn, A., and Lindauer, M. (2023)AutoRL Hyperparameter Landscapes. In Second International Conference on Automated Machine Learning, pp. 1–14.
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  • Glandorf*, P., Kaiser*, T., Rosenhahn, B., and (*contributed equally). (2023)HyperSparse Neural Networks: Shifting Exploration to Exploitation through Adaptive Regularization. In International Conference on Computer Vision Workshops (ICCVW).
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  • Kuhnke, F., and Ostermann, J. (2023)Domain Adaptation for Head Pose Estimation Using Relative Pose Consistency, IEEE Transactions on Biometrics, Behavior, and Identity Science.
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2022

  • Benjamins, C., Eimer, T., Schubert, F., Mohan, A., Biedenkapp, A., Rosenhahn, B., Hutter, F., and Lindauer, M. (2022)Contextualize Me - The Case for Context in Reinforcement Learning, ArXiv Preprint.
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  • Biswas, A., Patro, G. K., Ganguly, N., Gummadi, K. P., and Chakraborty, A. (2022)Toward Fair Recommendation in Two-sided Platforms, {ACM} Transactions on the Web, Association for Computing Machinery ({ACM}) 16, 1–34.
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  • Benjamins, C., Eimer, T., Schubert, F., Mohan, A., Biedenkapp, A., Rosenhahn, B., Hutter, F., and Lindauer, M. (2022)Contextualize Me -- The Case for Context in Reinforcement Learning, Arxiv Preprint, arXiv.
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  • Deng, D., Karl, F., Hutter, F., Bischl, B., and Lindauer, M. (2022)Efficient Automated Deep Learning for Time Series Forecasting. In Proceedings of the European Conference on Machine Learning (ECML), arXiv.
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  • Deng, D., and Lindauer, M. (2022)Searching in the Forest for Local Bayesian Optimization. In ECML/PKDD workshop on Meta-learning.
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  • Poker, Y., Hardenberg, S. V., Hofmann, W., Tang, M., Baumann, U., Schwerk, N., Wetzke, M., Lindenthal, V., Auber, B., Schlegelberger, B., Ott, H., Bismarck, P. V., Viemann, B., Dressler, F., Klemann, C., and Bergmann, A. K. (2022)Genetics in inborn errors of immunity: pediatric auto inflammatory phenotypes and the underlying genetic causes in 125 families. In .
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  • Lange, A., Hinrichs, R., and Ostermann, J. (2022)Localized Damage Detection in Wind Turbine Rotor Blades using Airborne Acoustic Emissions (accepted). In 9th Asia-Pacific Workshops on Structural Health Monitoring 2022 (APWSHM 2022).
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  • Xuan, Q. L., Adhisantoso, Y. G., Munderloh, M., and Ostermann, J. (2022)Uncertainty-Aware Remaining Useful Life Prediction for Predictive Maintenance Using Deep Learning (accepted). In 16th CIRP Conference on Intelligent Computation in Manufacturing Engineering, CIRP ICME.
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  • Dockhorn, A. (2022)Choosing Representation, Mutation, and Crossover in Genetic Algorithms, IEEE Computational Intelligence Magazine 17, 52–53.
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2021

  • Hachmann, H., Kr{ü}ger, B., Rosenhahn, B., and Nogueira, W. (2021)Localization of Cochlear Implant Electrodes from Cone Beam Computed Tomography using Particle Belief Propagation. In International Symposium on Biomedical Imaging, ISBI.
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  • Hao, C., Liao, W., Tang, X., Yang, M. Y., Sester, M., and Rosenhahn, B. (2021)AMENet: Attentive Maps Encoder Network for Trajectory Prediction. In ISPRS Journal of Photogrammetry and Remote Sensing, pp. 253–266.
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  • Bellinghausen, C., Pletz, M. W., Rupp, J., Witzenrath, M., Welsch, C., Zeuzem, S., Trebicka, J., Rohde, G. G. U., and of the CAPNETZ study group, M. (2021)Chronic liver disease negatively affects outcome in hospitalised patients with community-acquired pneumonia, Gut 70, 221–222.
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  • Becker, M., Strengert, M., Junker, D., Kaiser, P. D., Kerrinnes, T., Traenkle, B., Dinter, H., Häring, J., Ghozzi, S., Zeck, A., Weise, F., Peter, A., Hörber, S., Fink, S., Ruoff, F., Dulovic, A., Bakchoul, T., Baillot, A., Lohse, S., Cornberg, M., Illig, T., Gottlieb, J., Smola, S., Karch, A., Berger, K., Rammensee, H.-G., Schenke-Layland, K., Nelde, A., Märklin, M., Heitmann, J. S., Walz, J. S., Templin, M., Joos, T. O., Rothbauer, U., Krause, G., and Schneiderhan-Marra, N. (2021)Exploring beyond clinical routine SARS-CoV-2 serology using MultiCoV-Ab to evaluate endemic coronavirus cross-reactivity, Nat Commun 12.
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  • Wandt, B., Rudolph, M., Zell, P., Rhodin, H., and Rosenhahn, B. (2021)CanonPose: Self-Supervised Monocular 3D Human Pose Estimation in the Wild. In Computer Vision and Pattern Recognition (CVPR).
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  • Chouvarine, P., Anti{{{\’c}}}, {\v{Z}}eljko, Lentes, J., Schröder, C., Alten, J., Brüggemann, M., de Santa Pau, E. C., Illig, T., Laguna, T., Schewe, D., Stanulla, M., Tang, M., Zimmermann, M., Schrappe, M., Schlegelberger, B., Cario, G., and Bergmann, A. K. (2021)Transcriptional and Mutational Profiling of B-Other Acute Lymphoblastic Leukemia for Improved Diagnostics, Cancers, {MDPI} {AG} 13, 5653.
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  • Hinrichs, R., Schmidt, A., Koslowski, J., Ostermann, J., and Denkena, B. (2021)Analysis of the impact of data compression on condition monitoring algorithms for ball screws. In CMMO CIRP 2021.
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  • He, S., Liao, W., Yang, M. Y., Yang, Y., Song, Y.-Z., Rosenhahn, B., and Xiang, T. (2021)Context-Aware Layout to Image Generation with Enhanced Object Appearance. In IEEE Conference on Computer Vision and Pattern Recognition.
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  • Souza, A., Nardi, L., Oliveira, L., Olukotun, K., Lindauer, M., and Hutter, F. (2021)Bayesian Optimization with a Prior for the Optimum. In Proceedings of the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML-PKDD).
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  • Zimmer, L., Lindauer, M., and Hutter, F. (2021)Auto-PyTorch Tabular: Multi-Fidelity MetaLearning for Efficient and Robust AutoDL, IEEE Transactions on Pattern Analysis and Machine Intelligence 43, 3079–3090.
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  • Cong, Y., Liao, W., Ackermann, H., Yang, M. Y., and Rosenhahn, B. (2021)Spatial-Temporal Transformer for Dynamic Scene Graph Generation. In International Conference on Computer Vision (ICCV).
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  • Narisetti, N., Henke, M., Seiler, C., Junker, A., Ostermann, J., Altmann, T., and Gladilin, E. (2021)Fully-automated root image analysis (faRIA), Scientific Reports 11.
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  • Warnstorf, D., Bawadi, R., Schienke, A., Strasser, R., Schmidt, G., Illig, T., Tauscher, M., Thol, F., Heuser, M., Steinemann, D., Davenport, C., Schlegelberger, B., Behrens, Y. L., and Göhring, G. (2021)Unbalanced translocation der(5;17) resulting in a TP53 loss as recurrent aberration in myelodysplastic syndrome and acute myeloid leukemia with complex karyotype, Genes Chromosomes Cancer 60, 452–457.
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  • Kluger, F., Ackermann, H., Brachmann, E., Yang, M. Y., and Rosenhahn, B. (2021)Cuboids Revisited: Learning Robust 3D Shape Fitting to Single RGB Images. In CVPR.
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  • Hartmann, F., Sommer, A., Pestel-Schiller, U., and Osterman, J. (2021)A scheme for stabilizing the image generation for VideoSAR. In 13th European Conference on Synthetic Aperture Radar.
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  • Hutter, F., Fuks, L., Lindauer, M., and Awad, N. (2021)Method, device and computer program for producing a strategy for a robot.
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  • Chin, T.-J., Suter, D., Ch’ng, S.-F., and Quach, J. (2021)Quantum Robust Fitting. In Computer Vision -- ACCV 2020 (Ishikawa, H., Liu, C.-L., Pajdla, T., and Shi, J., Eds.), pp. 485–499, Springer International Publishing, Cham.
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  • Nandy, A., Sharma, S., Maddhashiya, S., Sachdeva, K., Goyal, P., and Ganguly, N. (2021)Question Answering over Electronic Devices: A New Benchmark Dataset and a Multi-Task Learning based QA Framework, pp. 4600–4609, Association for Computational Linguistics.
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  • Schubert, F., Awiszus, M., and Rosenhahn, B. (2021)TOAD-GAN: a Flexible Framework for Few-Shot Level Generation in Token-Based Games, IEEE Transactions on Games.
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  • Samanta, B., Agrawal, M., and Ganguly, N. (2021)A Hierarchical VAE for Calibrating Attributes while Generating Text using Normalizing Flow, pp. 2405–2415, Association for Computational Linguistics.
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  • Benjak, M., Meuel, H., Laude, T., and Ostermann, J. (2021)Enhanced Machine Learning-based Inter Coding for VVC. In 2021 International Conference on Artificial Intelligence in Information and Communication (ICAIIC) (ICAIIC 2021).
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  • Tennakoon, R., Suter, D., Zhang, E., Chin, T.-J., and Bab-Hadiashar, A. (2021)Consensus Maximisation Using Influences of Monotone Boolean Functions. In 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 2865–2874.
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  • Mukherjee, R., Naik, A., Poddar, S., Dasgupta, S., and Ganguly, N. (2021)Understanding the Role of Affect Dimensions in Detecting Emotions from Tweets: A Multi-task Approach. In .
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  • Dong, N. T., Brogden, G., Gerold, G., and Khosla, M. (2021)A multitask transfer learning framework for the prediction of virus-human protein--protein interactions, BMC Bioinformatics 22, 572.
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  • Dockhorn, A., and Kruse, R. (2021)Fuzzy Modeling in Game AI, Journal of Pure and Applied Mathematics 12, 54–68.
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  • Decker, M., Lammens, T., Ferster, A., Erlacher, M., Yoshimi, A., Niemeyer, C. M., Ernst, M. P. T., Raaijmakers, M. H. G. P., Duployez, N., Flaum, A., Steinemann, D., Schlegelberger, B., Illig, T., and Ripperger, T. (2021)Functional classification of RUNX1 variants in familial platelet disorder with associated myeloid malignancies, Leukemia.
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  • Sheshadri, S., Saha, A., Patel, P., Datta, S., and Ganguly, N. (2021)Graph-based semi-supervised learning through the lens of safety. In Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence (de Campos, C., and Maathuis, M. H., Eds.), pp. 1576–1586, PMLR.
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  • Olatunji, I. E., Nejdl, W., and Khosla, M. (2021)Membership inference attack on graph neural networks. In IEEE International Conference on Trust, Privacy and Security in Intelligent Systems, and Applications (short version presented in ICLR-21 Workshop on Distributed and Private Machine Learning (DPML) ).
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  • Kellermann, C., Neumann, E., and Ostermann, J. (2021)A New Preprocessing Approach to Reduce Computational Complexity for Time Series Forecasting with Neuronal Networks: Temporal Resolution Warping. In 2021 International Symposium on Computer Science and Intelligent Controls (ISCSIC), pp. 324–328.
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  • Truong, G., Le, H., Suter, D., Zhang, E., and Gilani, S. Z. (2021)Unsupervised Learning for Robust Fitting: A Reinforcement Learning Approach. In 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 10343–10352.
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  • Booth, A., Reed, A. B., Ponzo, S., Yassaee, A., Aral, M., Plans, D., Labrique, A., and Mohan, D. (2021)Population risk factors for severe disease and mortality in COVID-19: A global systematic review and meta-analysis, PLOS ONE, Public Library of Science 16, 1–30.
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  • Dong, T., Brogden, G., Gerold, G., and Khosla, M. (2021)A multitask transfer learning framework for the prediction of virus-human protein-protein interactions, BMC Bioinformatics 22, 572.
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  • Singh, J., Wang, Z., Khosla, M., and Anand, A. (2021)Extracting per Query Valid Explanations for Blackbox Learning-to-Rank Models. In International Conference on the Theory of Information Retrieval.
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  • Gritzner, D., Hinrichs, H., Stetter, C., Wielert, H., Breitner, M. H., and Ostermann, J. (2021)Wind Turbine Localization in Satellite and Aerial Images. In Proceedings of the Wind Energy Science Conference 2021, pp. 40–41.
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  • Adhisantoso, Y. G. (2021)Cross-check CE3 Extension of Contact Matrix Compressor m58074, ISO/IEC JTC 1/SC 29/WG 8.
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  • Kellermann, C., and Ostermann, J. (2021)Estimation of unknown system states based on an adaptive neural network and Kalman filter, Procedia CIRP 99, 656–661.
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  • Dockhorn, A., Hurtado-Grueso, J., Jeurissen, D., Xu, L., and Perez-Liebana, D. (2021)Portfolio Search and Optimization for General Strategy Game-Playing. In 2021 IEEE Congress on Evolutionary Computation (CEC), pp. 2085–2092.
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  • Hachmann, H., Krüger, B., Rosenhahn, B., and Nogueira, W. (2021)Localization Of Cochlear Implant Electrodes From Cone Beam Computed Tomography Using Particle Belief Propagation. In 2021 IEEE 18th International Symposium on Biomedical Imaging (ISBI), pp. 593–597.
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  • Das, S., Patibandla, H., Bhattacharya, S., Bera, K., Ganguly, N., and Bhattacharya, S. (2021)TMCOSS: Thresholded Multi-Criteria Online Subset Selection for Data-Efficient Autonomous Driving. In ICCV.
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  • Ghosh, S., Ganguly, N., Mitra, B., and De, P. (2021)Designing an Experience Sampling Method for Smartphone Based Emotion Detection, IEEE Transactions on Affective Computing 12, 913–927.
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  • Ilyas, Z., Sharif, N., Schousboe, J. T., Lewis, J. R., Suter, D., and Gilani, S. Z. (2021)GuideNet: Learning Inter- Vertebral Guides in DXA Lateral Spine Images. In 2021 Digital Image Computing: Techniques and Applications (DICTA), pp. 01–07.
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  • Eimer, T., Biedenkapp, A., Hutter, F., and Lindauer, M. (2021)Self-Paced Context Evaluation for Contextual Reinforcement Learning. In Proceedings of the international conference on machine learning (ICML).
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  • Tan, D. W., Gilani, S. Z., Boutrus, M., Alvares, G. A., Whitehouse, A. J., Mian, A., Suter, D., and Maybery, M. T. (2021)Facial asymmetry in parents of children on the autism spectrum, Autism Research.
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  • Adhisantoso, Y. G. (2021)Verification of the Extension to the Coding of Contact Matrix m58073, ISO/IEC JTC 1/SC 29/WG 8.
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  • Kabongo, S., D’Souza, J., and Auer, S. (2021)Automated Mining of Leaderboards for Empirical {AI} Research, springer, International Conference on Asian Digital Libraries ICADL 2021: Towards Open and Trustworthy Digital Societies, 453–470.
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  • Dockhorn, A., and Kruse, R. (2021)Modelheuristics for efficient forward model learning, At-Automatisierungstechnik.
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  • Apeldoorn, D., and Dockhorn, A. (2021)Exception-Tolerant Hierarchical Knowledge Bases for Forward Model Learning, IEEE Transactions on Games 13, 249–262.
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  • Hinrichs, R., Dunkel, J., and Ostermann, J. (2021)Mixing Time-Frequency Distributions for Speech Command Recognition using Convolutional Neural Networks. In 6th International Conference on Frontiers of Signal Processing (ICFSP 2021).
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  • Schubert, F., Eimer, T., Rosenhahn, B., and Lindauer, M. (2021)Automatic Risk Adaptation in Distributional Reinforcement Learning. In Arxiv Preprint.
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  • Kellermann, C., Adhisantoso, Y. G., Munderloh, M., and Ostermann, J. (2021)Introduction to an Adaptive Remaining Useful Life Prediction for forming tools (accepted). In Proceedings of IEEE/ASME International Conference on Advanced Intelligent Mechatronics (AIM).
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  • Lindauer, M., Eggensperger, K., Feurer, M., Biedenkapp, A., Deng, D., Benjamins, C., Sass, R., and Hutter, F. (2021)SMAC3: A Versatile Bayesian Optimization Package for Hyperparameter Optimization. In ArXiv: 2109.09831.
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  • Gritzner, D., and Ostermann, J. (2021)Minimizing Manual Labeling Effort for The Semantic Segmentation of Aerial Images. In 2021 IEEE Statistical Signal Processing Workshop (SSP), pp. 81–85.
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  • Kuhnke, F., Ihler, S., and Ostermann, J. (2021)Relative Pose Consistency for Semi-Supervised Head Pose Estimation. In 16th IEEE International Conference on Automatic Face and Gesture Recognition (FG 2021).
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  • Speck, D., Biedenkapp, A., Hutter, F., Mattm{ü}ller, R., and Lindauer, M. (2021)Learning Heuristic Selection with Dynamic Algorithm Configuration. In Proceedings of the 31st International Conference on Automated Planning and Scheduling {(ICAPS’21)}.
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  • Biedenkapp, A., Rajan, R., Hutter, F., and Lindauer, M. (2021)TempoRL: Learning When to Act. In Proceedings of the international conference on machine learning (ICML).
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  • Moosbauer, J., Herbinger, J., Casalicchio, G., Lindauer, M., and Bischl, B. (2021)Explaining Hyperparameter Optimization via Partial Dependence Plots. In Proceedings of the international conference on Neural Information Processing Systems (NeurIPS).
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  • Voges, J., Hernaez, M., Mattavelli, M., and Ostermann, J. (2021)An Introduction to MPEG-G: The First Open ISO/IEC Standard for the Compression and Exchange of Genomic Sequencing Data, Proceedings of the IEEE 109, 1607–1622.
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  • Roy, S., Sural, S., Chhaya, N., Natarajan, A., and Ganguly, N. (2021)An Integrated Approach for Improving Brand Consistency of Web Content: Modeling, Analysis and Recommendation., ACM Trans. Web 15, 9:1–9:25.
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  • Benjamins, C., Eimer, T., Schubert, F., Biedenkapp, A., Rosenhahn, B., Hutter, F., and Lindauer, M. (2021)CARL: A Benchmark for Contextual and Adaptive Reinforcement Learning. In NeurIPS 2021 Workshop on Ecological Theory of Reinforcement Learning.
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  • Hornakova*, A., Kaiser*, T., Rolinek, M., Rosenhahn, B., Swoboda, P., Henschel, R., and equal contribution), (*. (2021)Making Higher Order MOT Scalable: An Efficient Approximate Solver for Lifted Disjoint Paths. In International Conference on Computer Vision (ICCV).
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  • Knura, M., Kluger, F., Zahtila, M., Schiewe, J., Rosenhahn, B., and Burghardt, D. (2021)Using Object Detection on Social Media Images for Urban Bicycle Infrastructure Planning: A Case Study of Dresden, ISPRS International Journal of Geo-Information.
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  • Liu, Z., Pavao, A., Xu, Z., Escalera, S., Ferreira, F., Gyon, I., Hong, S., Hutter, F., Ji, R., Junior, J. J., Li, G., Lindauer, M., Luo, Z., Madadi, M., Nierhoff, T., Niu, K., Pan, C., Stoll, D., Treguer, S., Jin, W., Wang, P., Wu, C., Youcheng, X., Zela, A., and Zhang, Y. (2021)Winning solutions and post-challenge analyses of the ChaLearn AutoDL challenge 2019, IEEE Transactions on Pattern Analysis and Machine Intelligence 1–18.
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  • Eimer, T., Biedenkapp, A., Reimer, M., Adriaensen, S., Hutter, F., and Lindauer, M. (2021)DACBench: A Benchmark Library for Dynamic Algorithm Configuration. In Proceedings of the international joint conference on artificial intelligence (IJCAI).
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  • Eggensperger, K., M{ü}ller, P., Mallik, N., Feurer, M., Sass, R., Klein, A., Awad, N., Lindauer, M., and Hutter, F. (2021)HPOBench: A Collection of Reproducible Multi-Fidelity Benchmark Problems for HPO. In Proceedings of the international conference on Neural Information Processing Systems (NeurIPS) (Datasets and Benchmarks Track).
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  • Mukherjee, R., Naik, A., Poddar, S., Dasgupta, S., and Ganguly, N. (2021)Understanding the Role of Affect Dimensions in Detecting Emotions from Tweets: A Multi-task Approach. In SIGIR 2021.
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  • Wehrbein, T., Rudolph, M., Rosenhahn, B., and Wandt, B. (2021)Probabilistic Monocular 3D Human Pose Estimation with Normalizing Flows. In International Conference on Computer Vision (ICCV).
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  • Koley, P., Saha, A., Bhattacharya, S., Ganguly, N., and De, A. (2021)Demarcating Endogenous and Exogenous Opinion Dynamics: An Experimental Design Approach, ACM Trans. Knowl. Discov. Data, Association for Computing Machinery, New York, NY, USA 15.
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  • Mukherjee, A., Mallick, M., Chakraborty, S., and Ganguly, N. (2021)Unsupervised Topology Assessment in Smart Homes. In 8th ACM IKDD CODS and 26th COMAD, pp. 193–197, Association for Computing Machinery, Bangalore, India.
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  • Nandy, A., Sharma, S., Maddhashiya, S., Sachdeva, K., Goyal, P., and Ganguly, N. (2021)Question Answering over Electronic Devices: A New Benchmark Dataset and a Multi-Task Learning based {QA} Framework. In Findings of the Association for Computational Linguistics: {EMNLP} 2021, Association for Computational Linguistics.
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  • Hornakova*, A., Kaiser*, T., Rosenhahn, B., Swoboda, P., Henschel, R., and equal contribution), (*. (2021)Higher Order Multiple Object Tracking for Crowded Scenes, Computer Vision and Pattern Recognition Workshops (CVPRW).
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  • Rumberg, L., Ehlert, H., L{ü}dtke, U., and Ostermann, J. (2021)Age-Invariant Training for End-to-End Child Speech Recognition using Adversarial Multi-Task Learning. In Proceedings INTERSPEECH 2021 -- 22th Annual Conference of the International Speech Communication Association.
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  • Benjak, M., Samayoa, Y., and Ostermann, J. (2021)Neural Network Based Error Concealment for VVC. In Proceedings of the 28th IEEE International Conference on Image Processing (ICIP).
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  • Gritzner, D., and Ostermann, J. (2021)Semantic Segmentation of Aerial Images Using Binary Space Partitioning. In KI 2021: Advances in Artificial Intelligence, pp. 116–134.
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  • Dockhorn, A., Hurtado-Grueso, J., Jeurissen, D., Xu, L., and Perez-Liebana, D. (2021)Game State and Action Abstracting Monte Carlo Tree Search for General Strategy Game-Playing. In Proceedings of the 2021 IEEE Conference on Games (CoG), pp. 1–8.
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  • Schubert, F., Eimer, T., Rosenhahn, B., and Lindauer, M. (2021)Towards Automatic Risk Adaption in Distributional Reinforcement Learning. In Reinforcement Learning for Real Life (RL4RealLife) Workshop in the 38th International Conference on Machine Learning (ICML).
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  • Pestel-Schiller, U., and Ostermann, J. (2021)Interpreter-Based Evaluation of Compressed SAR Images Using JPEG and HEVC Intra Coding: Compression Can Improve Usability. In 13th European Conference on Synthetic Aperture Radar.
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  • Dockhorn, A., Mostaghim, S., Kirst, M., and Zettwitz, M. (2021)Multi-Objective Optimization and Decision-Making in Context Steering. In 2021 IEEE Conference on Games (CoG), pp. 1–8.
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  • Liao, W., Lan, C., Yang, M. Y., Zeng, W., and Rosenhahn, B. (2021)Target-Tailored Source-Transformation for Scene Graph Generation. In In CVPR Workshop on Multi-Sensor Fusion for Dynamic Scene Understanding.
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  • Rudolph, M., Wandt, B., and Rosenhahn, B. (2021)Same Same But DifferNet: Semi-Supervised Defect Detection with Normalizing Flows. In Winter Conference on Applications of Computer Vision (WACV).
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  • Hartmann, F., and Ostermann, J. (2021)Investigation of the Effect of the Flight Path on the Three Dimensional Locatability of Targets. In Synthetic Aperture Radar (APSAR), 2021 IEEE 7th Asia-Pacific Conference.
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  • Moosbauer, J., Herbinger, J., Casalicchio, G., Lindauer, M., and Bischl, B. (2021)Towards Explaining Hyperparameter Optimization via Partial Dependence Plots. In Proceedings of the international workshop on Automated Machine Learning (AutoML) at ICML’21.
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  • Luo, C., Zhao, P., Qiao, B., Wu, Y., Zhang, H., Wu, W., Lu, W., Dang, Y., Rajmohan, S., Lin, Q., and Zhang, D. (2021)NTAM: Neighborhood-Temporal Attention Model for Disk Failure Prediction in Cloud Platforms. In Proceedings of the Web Conference 2021, {ACM}.
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  • Hinrichs, R., Gajecki, T., Ostermann, J., and Nogueira, W. (2021)A subjective and objective evaluation of a codec for the electrical stimulation patterns of cochlear implants, Journal of the Acoustic Society of America.
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  • Luo, C., Lin, J., Cai, S., Chen, X., He, B., Qiao, B., Zhao, P., Lin, Q., Zhang, H., Wu, W., Rajmohan, S., and Zhang, D. (2021)AutoCCAG: An Automated Approach to Constrained Covering Array Generation. In 2021 IEEE/ACM 43rd International Conference on Software Engineering (ICSE), pp. 201–212.
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  • Kaushal, A., Saha, A., and Ganguly, N. (2021)tWT–WT: A Dataset to Assert the Role of Target Entities for Detecting Stance of Tweets, pp. 3879–3889.
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  • Perez-Liebana, D., Guerrero-Romero, C., Dockhorn, A., Xu, L., Hurtado, J., and Jeurissen, D. (2021)Generating Diverse and Competitive Play-Styles for Strategy Games. In 2021 IEEE Conference on Games (CoG), pp. 1–8.
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  • Guerrero-Viu, J., Hauns, S., Izquierdo, S., Miotto, G., Schrodi, S., Biedenkapp, A., Elsken, T., Deng, D., Lindauer, M., and Hutter, F. (2021)Bag of Baselines for Multi-objective Joint Neural Architecture Search and Hyperparameter Optimization. In Proceedings of the international workshop on Automated Machine Learning (AutoML) at ICML’21.
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  • Adhisantoso, Y. G., and Ostermann, J. (2021)Method for the Coding of Contact Matrix m56622, ISO/IEC JTC 1/SC 29/WG 8.
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  • Awiszus, M., Schubert, F., and Rosenhahn, B. (2021)World-GAN: a Generative Model for Minecraft Worlds. In IEEE Conference on Games.
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  • Kadra, A., Lindauer, M., Hutter, F., and Grabocka, J. (2021)Regularization is all you Need: Simple Neural Nets can Excel on Tabular Data. In Proceedings of the international conference on Neural Information Processing Systems (NeurIPS).
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  • Eimer, T., Benjamins, C., and Lindauer, M. (2021)Hyperparameters in Contextual RL are Highly Situational. In NeurIPS 2021 Workshop on Ecological Theory of Reinforcement Learning.
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  • Roy, S., Chakraborty, S., Mandal, A., Balde, G., Sharma, P., Natarajan, A., Khosla, M., Sural, S., and Ganguly, N. (2021)Knowledge-Aware Neural Networks for Medical Forum Question Classification. In Proceedings of the 30th ACM International Conference on Information & Knowledge Management, pp. 3398–3402, Association for Computing Machinery, New York, NY, USA.
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  • Pestel-Schiller, U., Hu, K., Gritzner, D., and Ostermann, J. (2021)Determination of Relevant Hyperspectral Bands Using a Spectrally Constrained CNN. In 11th Workshop on Hyperspectral Imaging and Signal Processing: Evolution in Remote Sensing (WHISPERS), Paper 15.
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  • Holzapfel, C., Sag, S., Graf-Schindler, J., Fischer, M., Drabsch, T., Illig, T., Grallert, H., Stecher, L., Strack, C., Caterson, I., Jebb, S., Hauner, H., and Baessler, A. (2021)Association between single nucleotide polymorphisms and weight reduction in behavioural interventions—a pooled analysis, Nutrients, MDPI 13.
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  • Wu, W., Li, B., Luo, C., and Nejdl, W. (2021)Hashing-Accelerated Graph Neural Networks for Link Prediction. In .
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  • Adhisantoso, Y. G., and Ostermann, J. (2021)Efficient Coding of Contact Matrices m57789, ISO/IEC JTC 1/SC 29/WG 8.
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  • Zhao, B., van der Aa, H., Nguyen, T. T., Nguyen, Q. V. H., and Weidlich, M. (2021){EIRES}: Efficient Integration of Remote Data in Event Stream Processing. In Proceedings of the 2021 International Conference on Management of Data, {ACM}.
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  • Xue, Y., Kudenko, D., and Khosla, M. (2021)Graph Learning based Generation of Abstractions for Reinforcement Learning. In Adaptive and Learning Agents Workshop at AAMAS 2021.
    AbstractURLBibTeXEndNoteBibSonomy

2020

  • Zell, P., Rosenhahn, B., and Wandt, B. (2020)Weakly-supervised Learning of Human Dynamics. In European Conference on Computer Vision (ECCV).
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  • Henschel, R., von Marcard, T., and Rosenhahn, B. (2020)Accurate Long-Term Multiple People Tracking using Video and Body-Worn IMUs, IEEE Transactions on Image Processing.
    URLBibTeXEndNoteBibSonomy
  • Hu, T., Iosifidis, V., Wentong, L., Hang, Z., Yang, M. Y., Ntoutsi, E., and Rosenhahn, B. (2020)FairNN - Conjoint Learning of Fair Representations for Fair Decisions. In 23rd International Conference on Discovery Science.
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  • Krause, L., Koc, J., Rosenhahn, B., and Rosenhahn, A. (2020)Fully Convolutional Neural Network for Detection and Counting of Diatoms on Coatings after Short-Term Field Exposure, Environmental Science and Technology 54, 10022–10030.
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  • Cheng, H., Liao, W., Ying, Y. M., Sester, M., and Rosenhahn, B. (2020)MCENET: Multi-Context Encoder Network for Homogeneous Agent Trajectory Prediction in Mixed Traffic. In 23rd International Conference on Intelligent Transportation Systems (ITSC).
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  • Cong, Y., Ackermann, H., Liao, W., Yang, M. Y., and Rosenhahn, B. (2020)NODIS: Neural Ordinary Differential Scene Understanding. In European Conference on Computer Vision (ECCV).
    URLBibTeXEndNoteBibSonomy
  • Sen, H., Wentong, L., Tavakoli, H. R., Yang, M. Y., Rosenhahn, B., and Pugeault, N. (2020)Image Captioning through Image Transformer. In Asian Conference on Computer Vision (ACCV).
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  • Souza, A., Nardi, L., Oliveira, L., Olukotun, K., Lindauer, M., and Hutter, F. (2020)Prior-guided Bayesian Optimization. In arxiv:2006.14608[cs.LG].
    URLBibTeXEndNoteBibSonomy
  • Krause, T., and Ostermann, J. (2020)Damage Detection for Wind Turbine Rotor Blades Using Airborne Sound, Structural Control and Health Monitoring.
    URLBibTeXEndNoteBibSonomy
  • Kluger, F., Brachmann, E., Ackermann, H., Rother, C., Yang, M. Y., and Rosenhahn, B. (2020)CONSAC: Robust Multi-Model Fitting by Conditional Sample Consensus. In Computer Vision and Pattern Recognition (CVPR).
    URLBibTeXEndNoteBibSonomy
  • Awiszus, M., Schubert, F., and Rosenhahn, B. (2020, October)TOAD-GAN: Coherent Style Level Generation from a Single Example.
    AbstractURLBibTeXEndNoteBibSonomy
  • Rudolph, M., Wandt, B., and Rosenhahn, B. (2020, August)Same Same But DifferNet: Semi-Supervised Defect Detection with Normalizing Flows..
    AbstractURLBibTeXEndNoteBibSonomy
  • Liao, W., Cheng, X., Yang, J., Roth, S., Goesele, M., Yang, M. Y., and Rosenhahn, B. (2020)LR-CNN: Local-aware Region CNN for Vehicle Detection in Aerial Imagery. In XXIV ISPRS Congress, p. 8.
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  • Ackermann, H., Meuel, H., Rosenhahn, B., and Ostermann, J. (2020)Verfahren und Vorrichtung zum Aufnehmen eines Digitalbildes 1–12.
    URLBibTeXEndNoteBibSonomy
  • Meuel, H., and Ostermann, J. (2020)Analysis of Affine Motion-Compensated Prediction in Video Coding, IEEE Transactions on Image Processing 29, 7359–7374.
    URLBibTeXEndNoteBibSonomy
  • Samayoa, Y., and Ostermann, J. (2020)Modified Active Constellation Extension Algorithm for PAPR Reduction in OFDM Systems. In 2020 Wireless Telecommunications Symposium (WTS), p. 5.
    BibTeXEndNoteBibSonomy
  • Ostermann, J., and Hinrichs, R. (2020)Links und rechts verbinden, Unimagazin.
    URLBibTeXEndNoteBibSonomy
  • Perez-Liebana, D., Dockhorn, A., Grueso, J. H., and Jeurissen, D. (2020)The Design Of “Stratega”: A General Strategy Games Framework, arXiv:2009.05643 1–7.
    URLBibTeXEndNoteBibSonomy
  • Hu, T., Iosifidis, V., Liao, W., Zhang, H., Yang, M. Y., Ntoutsi, E., and Rosenhahn, B. (2020)FairNN - Conjoint Learning of Fair Representations for Fair Decisions.. In Discovery Science, pp. 581–595, Springer International Publishing.
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  • Biedenkapp, A., Rajan, R., Hutter, F., and Lindauer, M. (2020)Towards TempoRL: Learning When to Act. In Workshop on Inductive Biases, Invariances and Generalization in Reinforcement Learning (BIG@ICML’20).
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  • Feurer, M., Eggensperger, K., Falkner, S., Lindauer, M., and Hutter, F. (2020)Auto-Sklearn 2.0: The Next Generation. In arXiv:2007.04074 [cs.LG].
    URLBibTeXEndNoteBibSonomy
  • Pestel-Schiller, U., and Ostermann, J. (2020)Interpreter-Based Evaluation of Compressed SAR Images Using JPEG and HEVC Intra Coding: Compression Can Improve Usability. In 13th European Conference on Synthetic Aperture Radar.
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  • Voges, J., Paridaens, T., M{ü}ntefering, F., Mainzer, L. S., Bliss, B., Yang, M., Ochoa, I., Fostier, J., Ostermann, J., and Hernaez, M. (2020)GABAC: an arithmetic coding solution for genomic data, Bioinformatics 36, 2275–2277.
    URLBibTeXEndNoteBibSonomy
  • Awad, N., Shala, G., Deng, D., Mallik, N., Feurer, M., Eggensperger, K., Biedenkapp, A., Vermetten, D., Wang, H., Carola, D., Lindauer, M., and Hutter, F. (2020)Squirrel: A Switching Hyperparameter Optimizer, arxiv.
    URLBibTeXEndNoteBibSonomy
  • Kuhnke, F., Rumberg, L., and Ostermann, J. (2020)Two-Stream Aural-Visual Affect Analysis in the Wild. In 15th IEEE International Conference on Automatic Face and Gesture Recognition (FG 2020), pp. 366–371.
    URLBibTeXEndNoteBibSonomy
  • Denkena, B., Dittrich, M., Lindauer, M., Mainka, and St{ü}renburg, L. (2020)Using AutoML to Optimize Shape Error Prediction in Milling Processes. In Proceedings of 20th Machining Innovations Conference for Aerospace Industry (MIC).
    URLBibTeXEndNoteBibSonomy
  • Hornakova*, A., Henschel*, R., Rosenhahn, B., Swoboda, P., and equal contribution), (*. (2020)Lifted Disjoint Paths with Application in Multiple Object Tracking, Proceedings of the 37th International Conference on Machine Learning (ICML).
    URLBibTeXEndNoteBibSonomy
  • Adhisantoso, Y. G., Rohlfing, C., Voges, J., and Ostermann, J. (2020)Extension to method for the coding of genomic variants m55355, ISO/IEC JTC 1/SC 29/WG 8.
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  • Shala, G., Biedenkapp, A., Awad, N., Adriaensen, S., Lindauer, M., and Hutter, F. (2020)Learning Step-Size Adaptation in CMA-ES. In Proceedings of the Sixteenth International Conference on Parallel Problem Solving from Nature ({PPSN}’20).
    URLBibTeXEndNoteBibSonomy
  • Kluger, F., Ackermann, H., Yang, M. Y., and Rosenhahn, B. (2020)Temporally Consistent Horizon Lines. In International Conference on Robotics and Automation (ICRA).
    URLBibTeXEndNoteBibSonomy
  • Benjak, M., and Ostermann, J. (2020)Applications suitable for AI-based data compression, 1st Meeting of ISO/IEC JTC 1/SC 29/WG 2 Document m55424.
    BibTeXEndNoteBibSonomy
  • Wallat, J., Singh, J., and Anand, A. (2020)BERTnesia: Investigating the capture and forgetting of knowledge in BERT.. In Proceedings of the Third BlackboxNLP Workshop on Analyzing and Interpreting Neural Networks for NLP, pp. 174–183, Association for Computational Linguistics, Online.
    AbstractURLBibTeXEndNoteBibSonomy
  • Dockhorn, A., Grueso, J. H., Jeurissen, D., and Perez-Liebana, D. (2020)“Stratega”: A General Strategy Games Framework. In Joint Proceedings of the AIIDE 2020 Workshops co-located with 16th AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment (AIIDE 2020); Artificial Intelligence for Strategy Games, pp. 1–7.
    URLBibTeXEndNoteBibSonomy
  • Gaina, R. D., Balla, M., Dockhorn, A., Montoliu, R., and Perez liebana, D. (2020)TAG : A Tabletop Games Framework. In Joint Proceedings of the AIIDE 2020 Workshops co-located with 16th AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment (AIIDE 2020); CEUR Workshop Proceedings (2020), pp. 1–7.
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  • Wallat, J., Singh, J., and Anand, A. (2020)BERTnesia: Investigating the capture and forgetting of knowledge in BERT. In Proceedings of the Third BlackboxNLP Workshop on Analyzing and Interpreting Neural Networks for NLP, BlackboxNLP@EMNLP 2020, Online, November 2020 (Alishahi, A., Belinkov, Y., Chrupala, G., Hupkes, D., Pinter, Y., and Sajjad, H., Eds.), pp. 174–183, Association for Computational Linguistics.
    URLBibTeXEndNoteBibSonomy
  • Gritzner, D., and Ostermann, J. (2020)USING SEMANTICALLY PAIRED IMAGES TO IMPROVE DOMAIN ADAPTATION FOR THE SEMANTIC SEGMENTATION OF AERIAL IMAGES, ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences 483–492.
    URLBibTeXEndNoteBibSonomy
  • Luo, C., Zhao, P., Chen, C., Qiao, B., Du, C., Zhang, H., Wu, W., Cai, S., He, B., Rajmohan, S., and Lin, Q. (2020)PULNS: Positive-Unlabeled Learning with Effective Negative Sample Selector. In , pp. 8784–8792.
    AbstractURLBibTeXEndNoteBibSonomy
  • Tan, D., Maybery, M., Gilani, S. Z., Alvares, G., Mian, A., Suter, D., and Whitehouse, A. (2020)A broad autism phenotype expressed in facial morphology, Translational Psychiatry 10.
    BibTeXEndNoteBibSonomy
  • Dockhorn, A. (2020)Vorhersagebasierte Suche f{ü}r autonomes Spielen, pp. 69–78, GI.
    URLBibTeXEndNoteBibSonomy
  • Minh, C. N. D., Gilani, S. Z., Islam, S., and Suter, D. (2020)Learning Affordance Segmentation: An Investigative Study. In DICTA2020.
    BibTeXEndNoteBibSonomy
  • Dockhorn, A., Saxton, C., and Kruse, R. (2020)Association Rule Mining for Unknown Video Games, Fuzzy Approaches for Soft Computing and Approximate Reasoning: Theories and Applications 257–270.
    URLBibTeXEndNoteBibSonomy
  • Dockhorn, A., and Kruse, R. (2020)Forward Model Learning for Motion Control Tasks. In 2020 IEEE 10th International Conference on Intelligent Systems (IS), pp. 1–5.
    URLBibTeXEndNoteBibSonomy
  • Wulff, A., Mast, M., Hassler, M., Montag, S., Marschollek, M., and Jack, T. (2020)Designing an openEHR-Based Pipeline for Extracting and Standardizing Unstructured Clinical Data Using Natural Language Processing, Methods Inf Med 59, e64-e78.
    AbstractURLBibTeXEndNoteBibSonomy
  • {Fayyazifar}, N., {Ahderom}, S., {Suter}, D., {Maiorana}, A., and {Dwivedi}, G. (2020)Impact of Neural Architecture Design on Cardiac Abnormality Classification Using 12-lead ECG Signals. In 2020 Computing in Cardiology, pp. 1–4.
    BibTeXEndNoteBibSonomy
  • Dockhorn, A. (2020)Dissertation: Prediction-based Search for Autonomous Game-Playing, Otto von Guericke University Magdeburg 1–231.
    URLBibTeXEndNoteBibSonomy
  • Reinders, C., and Rosenhahn, B. (2020)Neuronale Netze: Angriffe und Verteidigung - Ich sehe was, was du nicht siehst, iX Developer 2020 – Machine Learning 2.0.
    BibTeXEndNoteBibSonomy
  • Dockhorn, A., and Lucas, S. (2020)Local Forward Model Learning for GVGAI Games. In IEEE Conference on Computational Intelligence and Games, CIG, pp. 716–723.
    URLBibTeXEndNoteBibSonomy
  • Dockhorn, A., and Kruse, R. (2020)Predicting Cards Using a Fuzzy Multiset Clustering of Decks, International Journal of Computational Intelligence Systems (IJCIS) 13, 1207–1217.
    URLBibTeXEndNoteBibSonomy
  • Samayoa, Y., and Ostermann, J. (2020)Parameter Selection for a Video Communication System based on HEVC and Channel Coding. In IEEE Latin-American Conference on Communications (LATINCOM 2020), p. 5.
    BibTeXEndNoteBibSonomy
  • Gaina, R. D., Balla, M., Dockhorn, A., Montoliu, R., and Perez-Liebana, D. (2020)Design and Implementation of TAG: A Tabletop Games Framework., arXiv:2009.12065.
    URLBibTeXEndNoteBibSonomy
  • Eimer, T., Biedenkapp, A., Hutter, F., and Lindauer, M. (2020)Towards Self-Paced Context Evaluations for Contextual Reinforcement Learning. In Workshop on Inductive Biases, Invariances and Generalization in Reinforcement Learning (BIG@ICML’20).
    BibTeXEndNoteBibSonomy
  • S{ü}dbeck, S., Krause, T., and Ostermann, J. (2020)Non-Line-of-Sight Time-Difference-of-Arrival Localization with Explicit Inclusion of Geometry Information in a Simple Diffraction Scenario. In IEEE MMSP 2020 - IEEE International Workshop on Multimedia Signal Processing.
    BibTeXEndNoteBibSonomy
  • Gebauer, C., and Bennewitz, M. (2020)Penalized Bootstrapping for Reinforcement Learning in Robot Control. In International Conference on Machine Learning and Applications (CMLA).
    BibTeXEndNoteBibSonomy
  • Zimmer, L., Lindauer, M., and Hutter, F. (2020)Auto-PyTorch Tabular: Multi-Fidelity MetaLearning for Efficient and Robust AutoDL. In arxiv:2006.13799[cs.LG].
    URLBibTeXEndNoteBibSonomy
  • Speck, D., Biedenkapp, A., Hutter, F., Mattm{ü}ller, R., and Lindauer, M. (2020)Learning Heuristic Selection with Dynamic Algorithm Configuration. In Proceedings of international workshop on Bridging the Gap Between AI Planning and Reinforcement Learning at ICAPS.
    URLBibTeXEndNoteBibSonomy
  • Adhisantoso, Y. G., Rohlfing, C., Voges, J., and Ostermann, J. (2020)Method for the coding of genotype likelihood of variant m55356, ISO/IEC JTC 1/SC 29/WG 8.
    BibTeXEndNoteBibSonomy
  • Hartmann, F., Sommer, A., Pestel-Schiller, U., and Osterman, J. (2020)A scheme for stabilizing the image generation for VideoSAR. In 13th European Conference on Synthetic Aperture Radar.
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  • Liu, Z., Pavao, A., Xu, Z., Escalera, S., Ferreira, F., Guyon, I., Hong, S., Hutter, F., Ji, R., Jacques, J., Li, G., Lindauer, M., Luo, Z., Madadi, M., Nierhoff, T., Niu, K., Pan, C., Stoll, D., Treguer, S., Wang, J., Wang, P., Wu, C., Xiong, Y., Zela, A., and Zhang, Y. (2020)Winning solutions and post-challenge analyses of the ChaLearn AutoDL challenge 2019. In HAL.
    URLBibTeXEndNoteBibSonomy
  • Sen, H., Wentong, L., Rezazadegan Tavakoli, H., Ying Yang, M., Rosenhahn, B., and Pugeault, N. (2020)Image Captioning through Image Transformer. In .
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  • Scheffner, I., Gietzelt, M., Abeling, T., Marschollek, M., and Gwinner, W. (2020)Patient Survival After Kidney Transplantation: Important Role of Graft-sustaining Factors as Determined by Predictive Modeling Using Random Survival Forest Analysis, Transplantation 104, 1095–1107.
    AbstractBibTeXEndNoteBibSonomy
  • Gra{{\"s}}hof, S., Ackermann, H., Brandt, S., and Ostermann, J. (2020)Multilinear Modelling of Faces and Expressions, Transactions on Pattern Analysis and Machine Intelligence (TPAMI).
    URLBibTeXEndNoteBibSonomy
  • J{ü}rgens, H., Hinrichs, R., and Ostermann, J. (2020)Recognizing Guitar Effects and Their Parameter Settings. In Proceedings of the DAFx2020 (Vol I).
    BibTeXEndNoteBibSonomy
  • Awiszus, M., Schubert, F., and Rosenhahn, B. (2020)TOAD-GAN: Coherent Style Level Generation from a Single Example. In AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment Best Student Paper Award.
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  • Eggensperger, K., Haase, K., M{ü}ller, P., Lindauer, M., and Hutter, F. (2020)Neural Model-based Optimization with Right-Censored Observations. In CoRR.
    URLBibTeXEndNoteBibSonomy

2019

  • Ostermann, J., Denkena, B., Bergmann, B., Schmidt, A., Krause, T., and Voges, J. (2019)Compression of Machine Tool Data, ISO/IEC JTC1/SC29/WG11.
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  • Dockhorn, A., Lucas, S. M., Volz, V., Bravi, I., Gaina, R. D., and Perez-Liebana, D. (2019)Learning Local Forward Models on Unforgiving Games. In 2019 IEEE Conference on Games (CoG).
    URLBibTeXEndNoteBibSonomy
  • Dengel, R., Woiwode, D., Florsch{ü}tz, N., Huber, V., Muller, T., von Pichowski, J., Rabinowitsch, A., Scholz, S., Sch{ü}lein, H., Steinweg, E., Stippel, B., St{ö}ferle, P., Wittekind, I., Wizemann, O., Zaft, A., Zembrot, L., and Griebenow, K. (2019)QUEST ON BEXUS 27. In 24th ESA Symposium on European Rocket \& Balloon Programmes and Related.
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  • Dockhorn, A., and Mostaghim, S. (2019)Introducing the Hearthstone-AI Competition, arXiv:1906.04238 1–4.
    URLBibTeXEndNoteBibSonomy
  • Wilbers, D., Rumberg, L., and Stachniss, C. (2019)Approximating marginalization with sparse global priors for sliding window SLAM-graphs.. In 2019 Third IEEE International Conference on Robotic Computing (IRC), pp. 25–31.
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  • Dockhorn, A., Schwensfeier, T., and Kruse, R. (2019)Fuzzy Multiset Clustering for Metagame Analysis. In Proceedings of the 11th Conference of the European Society for Fuzzy Logic and Technology (EUSFLAT 2019), pp. 536–543.
    URLBibTeXEndNoteBibSonomy
  • Lucas, S. M., Alexander, Dockhorn, V., Gaina, R. D., Bravi, I., Perez-Liebana, D., Mostaghim, S., and Kruse, R. (2019)A Local Approach to Forward Model Learning: Results on the Game of Life Game. In 2019 IEEE Conference on Games (CoG), pp. 1–8.
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2018

  • Dockhorn, A., Frick, M., Akkaya, {Ü}nal, and Kruse, R. (2018)Predicting Opponent Moves for Improving Hearthstone AI. In 17th International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems, IPMU 2018, pp. 621–632.
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  • Waltermann, C., Bethmann, K., Doering, A., Jjang, Y., Baumann, A. L., Anglemahr, M., and Schade, W. (2018)Multiple off-axis fiber Bragg gratings for 3D shape sensing, Applied Optics.
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  • Dockhorn, A., and Kruse, R. (2018)Detecting Sensor Dependencies for Building Complementary Model Ensembles. In Proceedings of the 28. Workshop Computational Intelligence, Dortmund, 29.-30. November 2018, pp. 217–234.
    URLBibTeXEndNoteBibSonomy
  • Pichler, E., Bethmann, K., Kelb, C., and Schade, W. (2018)Rapid prototyping of all-polymer AWGs for FBG readout using direct laser lithography, Optics Letters.
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  • Dockhorn, A., Tippelt, T., and Kruse, R. (2018)Model Decomposition for Forward Model Approximation. In 2018 IEEE Symposium Series on Computational Intelligence (SSCI), pp. 1751–1757.
    URLBibTeXEndNoteBibSonomy
  • Dockhorn, A., and Apeldoorn, D. (2018)Forward Model Approximation for General Video Game Learning. In Proceedings of the 2018 IEEE Conference on Computational Intelligence and Games (CIG’18), pp. 425–432.
    URLBibTeXEndNoteBibSonomy
  • Sabsch, T., Braune, C., Dockhorn, A., and Kruse, R. (2018)Using a multiobjective genetic algorithm for curve approximation. In 2017 IEEE Symposium Series on Computational Intelligence, SSCI 2017 - Proceedings, pp. 1–6.
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2017

  • Dockhorn, A., Doell, C., Hewelt, M., and Kruse, R. (2017)A decision heuristic for Monte Carlo tree search doppelkopf agents. In 2017 IEEE Symposium Series on Computational Intelligence (SSCI), pp. 1–8.
    URLBibTeXEndNoteBibSonomy
  • Dockhorn, A., and Kruse, R. (2017)Combining cooperative and adversarial coevolution in the context of pac-man. In 2017 IEEE Conference on Computational Intelligence and Games, CIG 2017, pp. 60–67.
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2016

  • Dockhorn, A., Braune, C., and Kruse, R. (2016)Variable density based clustering. In 2016 IEEE Symposium Series on Computational Intelligence (SSCI), pp. 1–8.
    URLBibTeXEndNoteBibSonomy
  • Orighici, R., Bethmann, K., Zywietz, U., Reinhard, C., and Schade, W. (2016)All-polymer arrayed waveguide gratings at 850 nm: design, fabrication and characterization, Optics Letters.
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2015

  • Pichler, E., Bethmann, K., Zywietz, U., Reinhard, C., Spad, C., Gleissner, U., Kelb, C., Roth, B., Willer, U., and Schade, W. (2015)Ring resonators in polymer foils for sensing of gaseous species. In Fiber Optic Sensors and Applications.
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  • Dockhorn, A., Braune, C., and Kruse, R. (2015)An Alternating Optimization Approach based on Hierarchical Adaptations of DBSCAN. In 2015 IEEE Symposium Series on Computational Intelligence (SSCI), pp. 749–755.
    URLBibTeXEndNoteBibSonomy
  • Waltermann, C., Baumann, A. L., Bethmann, K., Doering, A., Koch, J., Angelmahr, m., and Schade, W. (2015)Femtosecond laser processing of evanescence field coupled waveguides in single mode glass fibers for optical 3D shape sensing and navigation. In Fiber Optic Sensors and Applications.
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  • Bethmann, K., Orghici, R., Pichler, E., Zywietz, U., Reinhard, C., Schmidt, T., Gleissner, U., Kelb, C., Roth, B., Willer, U., and Schade, W. (2015)New design for a wavelength demultiplexing device. In Fiber Optic Sensors and Applications.
    BibTeXEndNoteBibSonomy
  • Dockhorn, A. (2015)Master Thesis: Hierarchical Extensions and Cluster Validation Techniques for DBSCAN, Otto von Guericke University Magdeburg 1–80.
    BibTeXEndNoteBibSonomy
  • Held, P., Dockhorn, A., Krause, B., and Kruse, R. (2015)Clustering Social Networks Using Competing Ant Hives. In 2015 Second European Network Intelligence Conference, pp. 67–74.
    URLBibTeXEndNoteBibSonomy
  • Held, P., Dockhorn, A., and Kruse, R. (2015)On Merging and Dividing Social Graphs, Journal of Artificial Intelligence and Soft Computing Research 5, 23–49.
    URLBibTeXEndNoteBibSonomy

2014

  • Held, P., Dockhorn, A., and Kruse, R. (2014)On Merging and Dividing of Barabasi-Albert-graphs. In 2014 IEEE Symposium on Evolving and Autonomous Learning Systems (EALS).
    URLBibTeXEndNoteBibSonomy
  • Held, P., Dockhorn, A., and Kruse, R. (2014)Generating Events for Dynamic Social Network Simulations. In Information Processing and Management of Uncertainty in Knowledge-Based Systems, pp. 46–55.
    URLBibTeXEndNoteBibSonomy
  • Dockhorn, A. (2014)Bachelor Thesis: Computergest{ü}tzte Analyse onkologischer Daten mithilfe Graphischer Modelle, Otto von Guericke University of Magdeburg 1–80.
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