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  • Maier, H. B., Neyazi, A., Bundies, G. L., Meyer-Bockenkamp, F., Bleich, S., Pathak, H., Ziert, Y., Neuhaus, B., M{ü}ller, F.-J., Pollmann, I., Illig, T., M{ü}cke, S., M{ü}ller, M., M{ö}ller, B. K., Oeltze-Jafra, S., Kacprowski, T., Voges, J., M{ü}ntefering, F., Scheiber, J., Reif, A., Aichholzer, M., Reif-Leonhard, C., Schmidt-Kassow, M., Hegerl, U., Reich, H., Unterecker, S., Weber, H., Deckert, J., B{ö}ssel-Debbert, N., Grabe, H. J., Lucht, M., and Frieling, H. (2024)Validation of the predictive value of BDNF -87 methylation for antidepressant treatment success in severely depressed patients—a randomized rater-blinded trial, Trials 25.
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  • Kluger, F., Brachmann, E., Yang, M. Y., and Rosenhahn, B. (2024)Robust Shape Fitting for 3D Scene Abstraction, IEEE Transactions on Pattern Analysis and Machine Intelligence.
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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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  • 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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  • 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.
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  • Kaiser, T., Reinders, C., and Rosenhahn, B. (2023)Compensation Learning in Semantic Segmentation. In Computer Vision and Pattern Recognition Workshops (CVPRW).
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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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  • 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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  • 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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  • 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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  • Rumberg, L., Gebauer, C., Ehlert, H., L{ü}dtke, U., and Ostermann, J. (2022)Improving Phonetic Transcriptions of Children’s Speech by Pronunciation Modelling with Constrained CTC-Decoding. In Proceedings INTERSPEECH 2022 – 23rd Annual Conference of the International Speech Communication Association.
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  • Hinrichs, R., Liang, K., Lu, Z., and Ostermann, J. (2022)Improved Compression of Artificial Neural Networks through Curvature-Aware Training. In Proceedings of the IEEE World Congress on Computational Intelligence.
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  • Schier, M., Reinders, C., and Rosenhahn, B. (2022)Constrained Mean Shift Clustering. In Proceedings of the 2022 SIAM International Conference on Data Mining (SDM).
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  • Xu, L., Hurtado-Grueso, J., Jeurissen, D., Liebana, D. P., and Dockhorn, A. (2022)Elastic Monte Carlo Tree Search State Abstraction for Strategy Game Playing. In 2022 IEEE Conference on Games (CoG).
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  • Dockhorn, A., and Kruse, R. (2022)Balancing Exploration and Exploitation in Forward Model Learning, Advances in Intelligent Systems Research and Innovation 1–19.
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  • Nayak, T., Sharma, S., Butala, Y., Dasgupta, K., Goyal, P., and Ganguly, N. (2022)A Generative Approach for Financial Causality Extraction. In Companion Proceedings of the Web Conference 2022, {ACM}.
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  • Pestel-Schiller, U., and Ostermann, J. (2022)Impact of Spatial Resolution and Zoom on Interpreter-Based Evaluation of Compressed SAR Images. In 14th European Conference on Synthetic Aperture Radar.
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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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  • 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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  • 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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  • 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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  • 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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  • 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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  • 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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  • 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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  • 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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  • 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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  • 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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  • Dockhorn, A., and Kruse, R. (2021)Modelheuristics for efficient forward model learning, At-Automatisierungstechnik.
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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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  • 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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  • 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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  • 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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  • 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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  • 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.
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  • 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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  • Ostermann, J., and Hinrichs, R. (2020)Links und rechts verbinden, Unimagazin.
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  • J{ü}rgens, H., Hinrichs, R., and Ostermann, J. (2020)Recognizing Guitar Effects and Their Parameter Settings. In Proceedings of the DAFx2020 (Vol I).
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  • 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).
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  • 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.
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  • Dockhorn, A. (2020)Vorhersagebasierte Suche f{ü}r autonomes Spielen, pp. 69–78, GI.
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  • 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.
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  • 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., 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.
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  • 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).
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