Uncertainty-driven Imagination for Continuous Deep Reinforcement Learning. - Gabriel Kalweit; Joschka Boedecker (CoRL, 2017)

Dynamic Input for Deep Reinforcement Learning in Autonomous Driving. - Maria Hügle; Gabriel Kalweit; Branka Mirchevska; Moritz Werling; Joschka Boedecker (IROS, 2019)

Off-policy Multi-step Q-learning. - Gabriel Kalweit; Maria Hügle; Joschka Boedecker (CoRR, 2019)

Dynamic Interaction-Aware Scene Understanding for Reinforcement Learning in Autonomous Driving. - Maria Hügle; Gabriel Kalweit; Moritz Werling; Joschka Boedecker (ICRA, 2020)

Adversarial Skill Networks: Unsupervised Robot Skill Learning from Video. - Oier Mees; Markus Merklinger; Gabriel Kalweit; Wolfram Burgard (ICRA, 2020)

Deep Inverse Q-learning with Constraints. - Gabriel Kalweit; Maria Hügle; Moritz Werling; Joschka Boedecker (NeurIPS, 2020)

Interpretable Multi Time-scale Constraints in Model-free Deep Reinforcement Learning for Autonomous Driving. - Gabriel Kalweit; Maria Hügle; Moritz Werling; Joschka Boedecker (CoRR, 2020)

A Dynamic Deep Neural Network For Multimodal Clinical Data Analysis. - Maria Hügle; Gabriel Kalweit; Thomas Huegle; Joschka Boedecker (CoRR, 2020)

Amortized Q-learning with Model-based Action Proposals for Autonomous Driving on Highways. - Branka Mirchevska; Maria Hügle; Gabriel Kalweit; Moritz Werling; Joschka Boedecker (ICRA, 2021)

AnyNets: Adaptive Deep Neural Networks for Medical Data with Missing Values. - Maria Kalweit; Gabriel Kalweit; Joschka Boedecker (AI4Function@IJCAI, 2021)

Q-learning with Long-term Action-space Shaping to Model Complex Behavior for Autonomous Lane Changes. - Gabriel Kalweit; Maria Hügle; Moritz Werling; Joschka Boedecker (IROS, 2021)

Latent Plans for Task-Agnostic Offline Reinforcement Learning. - Erick Rosete-Beas; Oier Mees; Gabriel Kalweit; Joschka Boedecker; Wolfram Burgard (CoRL, 2022)

Affordance Learning from Play for Sample-Efficient Policy Learning. - Jessica Borja-Diaz; Oier Mees; Gabriel Kalweit; Lukás Hermann; Joschka Boedecker; Wolfram Burgard (ICRA, 2022)

Deep Surrogate Q-Learning for Autonomous Driving. - Maria Kalweit; Gabriel Kalweit; Moritz Werling; Joschka Boedecker (ICRA, 2022)

Robust and Data-efficient Q-learning by Composite Value-estimation. - Gabriel Kalweit; Maria Kalweit; Joschka Boedecker (Trans. Mach. Learn. Res., 2022)

On the role of time horizons in reinforcement learning. - Gabriel Kalweit (2022)

Robust Tumor Detection from Coarse Annotations via Multi-Magnification Ensembles. - Mehdi Naouar; Gabriel Kalweit; Ignacio Mastroleo; Philipp Poxleitner; Marc Christian Metzger; Joschka Boedecker; Maria Kalweit (CoRR, 2023)

L(M)V-IQL: Multiple Intention Inverse Reinforcement Learning for Animal Behavior Characterization. - Hao Zhu; Brice De La Crompe; Gabriel Kalweit; Artur Schneider; Maria Kalweit; Ilka Diester; Joschka Boedecker (CoRR, 2023)

CellMixer: Annotation-free Semantic Cell Segmentation of Heterogeneous Cell Populations. - Mehdi Naouar; Gabriel Kalweit; Anusha Klett; Yannick Vogt; Paula Silvestrini; Diana Laura Infante Ramírez; Roland Mertelsmann; Joschka Boedecker; Maria Kalweit (CoRR, 2023)

Stable Online and Offline Reinforcement Learning for Antibody CDRH3 Design. - Yannick Vogt; Mehdi Naouar; Maria Kalweit; Christoph Cornelius Miething; Justus Duyster; Roland Mertelsmann; Gabriel Kalweit; Joschka Boedecker (CoRR, 2024)

BetterBodies: Reinforcement Learning guided Diffusion for Antibody Sequence Design. - Yannick Vogt; Mehdi Naouar; Maria Kalweit; Christoph Cornelius Miething; Justus Duyster; Joschka Boedecker; Gabriel Kalweit (CoRR, 2024)

Detection of disease-specific signatures in B cell repertoires of lymphomas using machine learning. - Paul Schmidt-Barbo; Gabriel Kalweit; Mehdi Naouar; Lisa Paschold; Edith Willscher; Christoph Schultheiß; Bruno Märkl; Stefan Dirnhofer; Alexandar Tzankov; Mascha Binder; Maria Kalweit (PLoS Comput. Biol., 2024)

Multi-intention Inverse Q-learning for Interpretable Behavior Representation. - Hao Zhu; Brice De La Crompe; Gabriel Kalweit; Artur Schneider; Maria Kalweit; Ilka Diester; Joschka Boedecker (Trans. Mach. Learn. Res., 2024)

Salvage: Shapley-distribution Approximation Learning Via Attribution Guided Exploration for Explainable Image Classification. - Mehdi Naouar; Hanne Raum; Jens Rahnfeld; Yannick Vogt; Joschka Boedecker; Gabriel Kalweit; Maria Kalweit (ICLR, 2025)

SR-Reward: Taking The Path More Traveled. - Seyed Mahdi B. Azad; Zahra Padar; Gabriel Kalweit; Joschka Boedecker (Trans. Mach. Learn. Res., 2025)