Key Publications
Arian Mousakhan, Sudhanshu Mittal, Silvio Galesso, Karim Farid, Thomas Brox, "Orbis: Overcoming Challenges of Long-Horizon Prediction in Driving World Models", Advances in Neural Information Processing Systems (NeurIPS), 2025.
Akshay L Chandra, Iman Nematollahi, Chenguang Huang, Tim Welschehold, Wolfram Burgard, Abhinav Valada, “DiWA: Diffusion Policy Adaptation with World Models”, Conference on Robot Learning (CoRL), 2025.
Simon Schrodi, David T. Hoffmann, Max Argus, V. Fischer, Thomas Brox, "Two Effects, One Trigger: On the Modality Gap, Object Bias, and Information Imbalance in Contrastive Vision-Language Models", International Conference on Learning Representations (ICLR), 2025.
Noah Hollmann, Samuel Müller, Lennart Purucker, Arjun Krishnakumar, Max Körfer, Shi Bin Hoo, Robin Tibor Schirrmeister, Frank Hutter, "Accurate predictions on small data with a tabular foundation model", Nature, 2025
Dominik Schreiber, Niccolò Rigi-Luperti, Armin Biere, "Streamlining Distributed SAT Solver Design", Intl. Conf. on Theory and Applications of Satisfiability Testing (SAT'25), Leibniz International Proceedings in Informatics (LIPIcs) vol. 341, pages 27:1-27:23, 2025.
Moritz Schneider, Robert Krug, Narunas Vaskevicius, Luigi Palmieri, Joschka Boedecker, "The surprising ineffectiveness of pre-trained visual representations for model-based reinforcement learning", Advances in Neural Information Processing Systems (NeurIPS), 2024.
Eugenio Chisari, Nick Heppert, Max Argus, Tim Welschehold, Thomas Brox, Abhinav Valada, “Learning Robotic Manipulation Policies from Point Clouds with Conditional Flow Matching”, Conference on Robot Learning (CoRL), 2024.
Katalin Fazekas, Aina Niemetz, Mathias Preiner, Markus Kirchweger, Stefan Szeider, Armin Biere, "Satisfiability Modulo User Propagators", Journal of Artificial Intelligence Research (JAIR), vol. 81, pages 989-1017, 2024.
Daniel Honerkamp, Tim Welschehold, Abhinav Valada, “N2M2: Learning Navigation for Arbitrary Mobile Manipulation Motions in Unseen and Dynamic Environments”, IEEE Transactions on Robotics (T-RO), vol. 39, no. 5, pp. 3601-3619, 2023.
Gabriel Kalweit, Maria Huegle, Moritz Werling, Joschka Boedecker, "Deep inverse Q-learning with constraints", Advances in Neural Information Processing Systems (NeurIPS), 2020.
Ilya Loshchilov, Frank Hutter, "Decoupled weight decay regularization", International Conference on Learning Representations (ICLR), 2019.
Olaf Ronneberger, Philipp Fischer, Thomas Brox, "U-Net: Convolutional Networks for Biomedical Image Segmentation", Medical Image Computing and Computer-Assisted Intervention (MICCAI), 2015.
Manuel Watter, Jost Tobias Springenberg, Joschka Boedecker, Martin Riedmiller, "Embed to control: A locally linear latent dynamics model for control from raw images", Advances in Neural Information Processing Systems (NeurIPS), 2015.
Chris Thornton, Frank Hutter, Holger Hoos, Kevin Leyton-Brown, "Auto-WEKA: Combined selection and hyperparameter optimization of classification algorithms", ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), 2013.
Niklas Eén, Armin Biere, "Effective Preprocessing in SAT through Variable and Clause Elimination", Intl. Conf. on Theory and Applications of Satisfiability Testing (SAT'05), Lecture Notes in Computer Science (LNCS), vol. 3569, Springer, 2005.
