Boedecker, Joschka

16 publications

TMLR 2025 Constrained Reinforcement Learning with Smoothed Log Barrier Function Baohe Zhang, Yuan Zhang, Hao Zhu, Shengchao Yan, Thomas Brox, Joschka Boedecker
TMLR 2025 Multi-BK-Net: Multi-Branch Multi-Kernel Convolutional Neural Networks for Clinical EEG Analysis Ann-Kathrin Kiessner, Tonio Ball, Joschka Boedecker
TMLR 2025 SR-Reward: Taking the Path More Traveled Seyed Mahdi B. Azad, Zahra Padar, Gabriel Kalweit, Joschka Boedecker
ICLR 2025 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
ICMLW 2024 Hierarchical Reinforcement Learning and Model Predictive Control for Strategic Motion Planning in Autonomous Racing Rudolf Reiter, Jasper Hoffmann, Joschka Boedecker, Moritz Diehl
ICMLW 2024 Learning When to Trust the Expert for Guided Exploration in RL Felix Schulz, Jasper Hoffmann, Yuan Zhang, Joschka Boedecker
TMLR 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
NeurIPS 2024 The Surprising Ineffectiveness of Pre-Trained Visual Representations for Model-Based Reinforcement Learning Moritz Schneider, Robert Krug, Narunas Vaskevicius, Luigi Palmieri, Joschka Boedecker
ICMLW 2024 Unsupervised Feature Extraction from a Foundation Model Zoo for Cell Similarity Search in Oncological Microscopy Across Devices Gabriel Kalweit, Anusha Klett, Mehdi Naouar, Jens Rahnfeld, Yannick Vogt, Diana Laura Infante Ramirez, Rebecca Berger, Jesus Duque Afonso, Tanja Nicole Hartmann, Marie Follo, Michael Luebbert, Roland Mertelsmann, Evelyn Ullrich, Joschka Boedecker, Maria Kalweit
CoRL 2023 Robust Reinforcement Learning in Continuous Control Tasks with Uncertainty Set Regularization Yuan Zhang, Jianhong Wang, Joschka Boedecker
CoRL 2022 Latent Plans for Task-Agnostic Offline Reinforcement Learning Erick Rosete-Beas, Oier Mees, Gabriel Kalweit, Joschka Boedecker, Wolfram Burgard
TMLR 2022 Robust and Data-Efficient Q-Learning by Composite Value-Estimation Gabriel Kalweit, Maria Kalweit, Joschka Boedecker
NeurIPSW 2021 Adaptively Calibrated Critic Estimates for Deep Reinforcement Learning Nicolai Dorka, Joschka Boedecker, Wolfram Burgard
NeurIPS 2020 Deep Inverse Q-Learning with Constraints Gabriel Kalweit, Maria Huegle, Moritz Werling, Joschka Boedecker
CoRL 2017 Uncertainty-Driven Imagination for Continuous Deep Reinforcement Learning Gabriel Kalweit, Joschka Boedecker
NeurIPS 2015 Embed to Control: A Locally Linear Latent Dynamics Model for Control from Raw Images Manuel Watter, Jost Springenberg, Joschka Boedecker, Martin Riedmiller