Gabriel Kalweit

Christoph Cornelius Miething

Justus Duyster

CoRR, 2024

Stable Online and Offline Reinforcement Learning for Antibody CDRH3 Design.

[BibT_eX]

[DOI]

Yannick Vogt

Mehdi Naouar

Christoph Cornelius Miething

CoRR, 2024

2023

CellMixer: Annotation-free Semantic Cell Segmentation of Heterogeneous Cell Populations.

[BibT_eX]

[DOI]

Diana Laura Infante Ramírez

Roland Mertelsmann

CoRR, 2023

L(M)V-IQL: Multiple Intention Inverse Reinforcement Learning for Animal Behavior Characterization.

[BibT_eX]

[DOI]

CoRR, 2023

Robust Tumor Detection from Coarse Annotations via Multi-Magnification Ensembles.

[BibT_eX]

[DOI]

Marc Christian Metzger

CoRR, 2023

2022

On the role of time horizons in reinforcement learning.

[BibT_eX]

[DOI]

PhD thesis, 2022

Robust and Data-efficient Q-learning by Composite Value-estimation.

[BibT_eX]

[DOI]

Trans. Mach. Learn. Res., 2022

Deep Surrogate Q-Learning for Autonomous Driving.

[BibT_eX]

[DOI]

Proceedings of the 2022 International Conference on Robotics and Automation, 2022

Affordance Learning from Play for Sample-Efficient Policy Learning.

[BibT_eX]

[DOI]

Proceedings of the 2022 International Conference on Robotics and Automation, 2022

Latent Plans for Task-Agnostic Offline Reinforcement Learning.

[BibT_eX]

[DOI]

Proceedings of the Conference on Robot Learning, 2022

2021

Q-learning with Long-term Action-space Shaping to Model Complex Behavior for Autonomous Lane Changes.

[BibT_eX]

[DOI]

Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, 2021

AnyNets: Adaptive Deep Neural Networks for Medical Data with Missing Values.

[BibT_eX]

[DOI]

Proceedings of the Second Workshop on Artificial Intelligence for Function, 2021

Amortized Q-learning with Model-based Action Proposals for Autonomous Driving on Highways.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Conference on Robotics and Automation, 2021

2020

A Dynamic Deep Neural Network For Multimodal Clinical Data Analysis.

[BibT_eX]

[DOI]

CoRR, 2020

Interpretable Multi Time-scale Constraints in Model-free Deep Reinforcement Learning for Autonomous Driving.

[BibT_eX]

[DOI]

CoRR, 2020

Deep Inverse Q-learning with Constraints.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Adversarial Skill Networks: Unsupervised Robot Skill Learning from Video.

[BibT_eX]

[DOI]

Proceedings of the 2020 IEEE International Conference on Robotics and Automation, 2020

Dynamic Interaction-Aware Scene Understanding for Reinforcement Learning in Autonomous Driving.

[BibT_eX]

[DOI]

Proceedings of the 2020 IEEE International Conference on Robotics and Automation, 2020

2019

Off-policy Multi-step Q-learning.

[BibT_eX]

[DOI]

Maria Hügle

CoRR, 2019

Dynamic Input for Deep Reinforcement Learning in Autonomous Driving.

[BibT_eX]

[DOI]

Proceedings of the 2019 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2019

2017

Uncertainty-driven Imagination for Continuous Deep Reinforcement Learning.

[BibT_eX]

[DOI]