Joschka Boedecker

CoRR, 2024

Constrained Reinforcement Learning with Smoothed Log Barrier Function.

[BibT_eX]

[DOI]

CoRR, 2024

Stable Online and Offline Reinforcement Learning for Antibody CDRH3 Design.

[BibT_eX]

[DOI]

Yannick Vogt

Mehdi Naouar

Christoph Cornelius Miething

CoRR, 2024

Reaching the ceiling? Empirical scaling behaviour for deep EEG pathology classification.

[BibT_eX]

[DOI]

Ann-Kathrin Kiessner

Comput. Biol. Medicine, 2024

The Surprising Ineffectiveness of Pre-Trained Visual Representations for Model-Based Reinforcement Learning.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

PlanNetX: Learning an efficient neural network planner from MPC for longitudinal control.

[BibT_eX]

[DOI]

Jasper Hoffmann

Diego Fernandez Clausen

Proceedings of the 6th Annual Learning for Dynamics & Control Conference, 2024

Safe Imitation Learning of Nonlinear Model Predictive Control for Flexible Robots.

[BibT_eX]

[DOI]

Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, 2024

Learning Continuous Control with Geometric Regularity from Robot Intrinsic Symmetry.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Conference on Robotics and Automation, 2024

Improving the Efficiency and Efficacy of Multi-Agent Reinforcement Learning on Complex Railway Networks with a Local-Critic Approach.

[BibT_eX]

[DOI]

Proceedings of the Thirty-Fourth International Conference on Automated Planning and Scheduling, 2024

UDUC: An Uncertainty-Driven Approach for Learning-Based Robust Control.

[BibT_eX]

[DOI]

Yuan Zhang

Jasper Hoffmann

Diana Laura Infante Ramírez

Proceedings of the ECAI 2024 - 27th European Conference on Artificial Intelligence, 19-24 October 2024, Santiago de Compostela, Spain, 2024

2023

The Treachery of Images: Bayesian Scene Keypoints for Deep Policy Learning in Robotic Manipulation.

[BibT_eX]

[DOI]

IEEE Robotics Autom. Lett., November, 2023

Adaptively Calibrated Critic Estimates for Deep Reinforcement Learning.

[BibT_eX]

[DOI]

IEEE Robotics Autom. Lett., 2023

Patient groups in Rheumatoid arthritis identified by deep learning respond differently to biologic or targeted synthetic DMARDs.

[BibT_eX]

[DOI]

PLoS Comput. Biol., 2023

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

[BibT_eX]

[DOI]

Roland Mertelsmann

Lukas Alexander Wilhelm Gemein

CoRR, 2023

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

[BibT_eX]

[DOI]

CoRR, 2023

Brain Age Revisited: Investigating the State vs. Trait Hypotheses of EEG-derived Brain-Age Dynamics with Deep Learning.

[BibT_eX]

[DOI]

CoRR, 2023

Geometric Regularity with Robot Intrinsic Symmetry in Reinforcement Learning.

[BibT_eX]

[DOI]

CoRR, 2023

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

[BibT_eX]

[DOI]

Marc Christian Metzger

CoRR, 2023

Incorporating Recurrent Reinforcement Learning into Model Predictive Control for Adaptive Control in Autonomous Driving.

[BibT_eX]

[DOI]

CoRR, 2023

Survey on LiDAR Perception in Adverse Weather Conditions.

[BibT_eX]

[DOI]

Proceedings of the IEEE Intelligent Vehicles Symposium, 2023

On the Calibration of Uncertainty Estimation in LiDAR-Based Semantic Segmentation.

[BibT_eX]

[DOI]

Mariella Dreissig

Florian Piewak

Proceedings of the 25th IEEE International Conference on Intelligent Transportation Systems, 2023

A Hierarchical Approach for Strategic Motion Planning in Autonomous Racing.

[BibT_eX]

[DOI]

Proceedings of the European Control Conference, 2023

Context-Conditional Navigation with a Learning-Based Terrain- and Robot-Aware Dynamics Model.

[BibT_eX]

[DOI]

Proceedings of the European Conference on Mobile Robots, 2023

Robust Reinforcement Learning in Continuous Control Tasks with Uncertainty Set Regularization.

[BibT_eX]

[DOI]

Yuan Zhang

Jianhong Wang

Proceedings of the Conference on Robot Learning, 2023

Imitation Learning from Nonlinear MPC via the Exact Q-Loss and its Gauss-Newton Approximation.

[BibT_eX]

[DOI]

Proceedings of the 62nd IEEE Conference on Decision and Control, 2023

2022

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

[BibT_eX]

[DOI]

Trans. Mach. Learn. Res., 2022

Correct Me If I am Wrong: Interactive Learning for Robotic Manipulation.

[BibT_eX]

[DOI]

IEEE Robotics Autom. Lett., 2022

On the calibration of underrepresented classes in LiDAR-based semantic segmentation.

[BibT_eX]

[DOI]

Mariella Dreissig

Florian Piewak

CoRR, 2022

Optimizing Trajectories for Highway Driving with Offline Reinforcement Learning.

[BibT_eX]

[DOI]

Branka Mirchevska

Moritz Werling

CoRR, 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

Adaptively Calibrated Critic Estimates for Deep Reinforcement Learning.

[BibT_eX]

[DOI]

Nicolai Dorka

Wolfram Burgard

CoRR, 2021

Residual Feedback Learning for Contact-Rich Manipulation Tasks with Uncertainty.

[BibT_eX]

[DOI]

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

Lukas Alexander Wilhelm Gemein

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

Machine-learning-based diagnostics of EEG pathology.

[BibT_eX]

[DOI]

Patryk Chrabaszcz

Daniel Wilson

Andreas Schulze-Bonhage

Frank Hutter

Lukas Dominique Josef Fiederer

NeuroImage, 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

Learning Human-Aware Robot Navigation from Physical Interaction via Inverse Reinforcement Learning.

[BibT_eX]

[DOI]

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

A service assistant combining autonomous robotics, flexible goal formulation, and deep-learning-based brain-computer interfacing.

[BibT_eX]

[DOI]

Daniel Kuhner

Johannes Aldinger

Felix Burget

Martin Völker

Lukas Dominique Josef Fiederer

Robotics Auton. Syst., 2019

VR-Goggles for Robots: Real-to-Sim Domain Adaptation for Visual Control.

[BibT_eX]

[DOI]

IEEE Robotics Autom. Lett., 2019

Adaptive long-term control of biological neural networks with Deep Reinforcement Learning.

[BibT_eX]

[DOI]

Neurocomputing, 2019

Hybrid Brain-Computer-Interfacing for Human-Compliant Robots: Inferring Continuous Subjective Ratings With Deep Regression.

[BibT_eX]

[DOI]

Martin Völker

Wolfram Burgard

Frontiers Neurorobotics, 2019

Off-policy Multi-step Q-learning.

[BibT_eX]

[DOI]

Maria Hügle

CoRR, 2019

Learning-based Model Predictive Control for Safe Exploration and Reinforcement Learning.

[BibT_eX]

[DOI]

CoRR, 2019

Scheduled Intrinsic Drive: A Hierarchical Take on Intrinsically Motivated Exploration.

[BibT_eX]

[DOI]

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

Multimodal Spatio-Temporal Information in End-to-End Networks for Automotive Steering Prediction.

[BibT_eX]

[DOI]

Mohamed Abou-Hussein

Stefan H. Müller

Proceedings of the International Conference on Robotics and Automation, 2019

2018

VR Goggles for Robots: Real-to-sim Domain Adaptation for Visual Control.

[BibT_eX]

[DOI]

CoRR, 2018

High-level Decision Making for Safe and Reasonable Autonomous Lane Changing using Reinforcement Learning.

[BibT_eX]

[DOI]

Proceedings of the 21st International Conference on Intelligent Transportation Systems, 2018

Early Seizure Detection with an Energy-Efficient Convolutional Neural Network on an Implantable Microcontroller.

[BibT_eX]

[DOI]

Andreas Schulze-Bonhage

Peter Woias

Proceedings of the 2018 International Joint Conference on Neural Networks, 2018

Prediction of electrocardiography features points using seismocardiography data: a machine learning approach.

[BibT_eX]

[DOI]

Proceedings of the 2018 ACM International Symposium on Wearable Computers, 2018

Controlling biological neural networks with deep reinforcement learning.

[BibT_eX]

[DOI]

Proceedings of the 26th European Symposium on Artificial Neural Networks, 2018

Hardware Implementation of a Performance and Energy-optimized Convolutional Neural Network for Seizure Detection.

[BibT_eX]

[DOI]

Andreas Schulze-Bonhage

Peter Woias

Proceedings of the 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2018

2017

Neural SLAM.

[BibT_eX]

[DOI]

CoRR, 2017

Deep reinforcement learning with successor features for navigation across similar environments.

[BibT_eX]

[DOI]

Jingwei Zhang

Lukas Dominique Josef Fiederer

Wolfram Burgard

Proceedings of the 2017 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2017

Predicting Time Series with Space-Time Convolutional and Recurrent Neural Networks.

[BibT_eX]

[DOI]

Proceedings of the 25th European Symposium on Artificial Neural Networks, 2017

Acting thoughts: Towards a mobile robotic service assistant for users with limited communication skills.

[BibT_eX]

[DOI]

Felix Burget

Daniel Kuhner

Martin Völker

Johannes Aldinger

Proceedings of the 2017 European Conference on Mobile Robots, 2017

Uncertainty-driven Imagination for Continuous Deep Reinforcement Learning.

[BibT_eX]

[DOI]

Proceedings of the 1st Annual Conference on Robot Learning, CoRL 2017, Mountain View, 2017

2016

Autonomous Optimization of Targeted Stimulation of Neuronal Networks.

[BibT_eX]

[DOI]

PLoS Comput. Biol., 2016

2015

Autonomous Learning of State Representations for Control: An Emerging Field Aims to Autonomously Learn State Representations for Reinforcement Learning Agents from Their Real-World Sensor Observations.

[BibT_eX]

[DOI]

Wendelin Böhmer

Martin A. Riedmiller

Klaus Obermayer

Künstliche Intell., 2015

Embed to Control: A Locally Linear Latent Dynamics Model for Control from Raw Images.

[BibT_eX]

[DOI]

Manuel Watter

Martin A. Riedmiller

Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

2014

Approximate real-time optimal control based on sparse Gaussian process models.

[BibT_eX]

[DOI]

Jan Wülfing

Martin A. Riedmiller

Proceedings of the 2014 IEEE Symposium on Adaptive Dynamic Programming and Reinforcement Learning, 2014

2013

On active information storage in input-driven systems

[BibT_eX]

[DOI]

CoRR, 2013

Guided Self-Organization of Input-Driven Recurrent Neural Networks.

[BibT_eX]

[DOI]

CoRR, 2013

2012

Information processing in echo state networks at the edge of chaos.

[BibT_eX]

[DOI]

Joseph T. Lizier

Theory Biosci., 2012

Real-Time Inverse Dynamics Learning for Musculoskeletal Robots based on Echo State Gaussian Process Regression.

[BibT_eX]

[DOI]

Proceedings of the Robotics: Science and Systems VIII, 2012

2011

Trying anyways: How ignoring the errors may help in learning new skills.

[BibT_eX]

[DOI]

Proceedings of the 1st International Conference on Development and Learning and on Epigenetic Robotics, 2011

Between Frustration and Elation: Sense of Control Regulates the lntrinsic Motivation for Motor Learning.

[BibT_eX]

[DOI]

Proceedings of the Lifelong Learning, 2011

2010

Improving Recurrent Neural Network Performance Using Transfer Entropy.

[BibT_eX]

[DOI]

Proceedings of the Neural Information Processing. Models and Applications, 2010

2009

Robot motion description and real-time management with the Harmonic Motion Description Protocol.

[BibT_eX]

[DOI]

Robotics Auton. Syst., 2009

Studies on reservoir initialization and dynamics shaping in echo state networks.

[BibT_eX]

[DOI]

Proceedings of the 17th European Symposium on Artificial Neural Networks, 2009

2007

HMDP: A New Protocol for Motion Pattern Generation Towards Behavior Abstraction.

[BibT_eX]

[DOI]

Proceedings of the RoboCup 2007: Robot Soccer World Cup XI, 2007

Introducing Physical Visualization Sub-league.

[BibT_eX]

[DOI]

Rodrigo da Silva Guerra

Proceedings of the RoboCup 2007: Robot Soccer World Cup XI, 2007

2006

3D2Real: Simulation League Finals in Real Robots.

[BibT_eX]

[DOI]

Rodrigo da Silva Guerra

Proceedings of the RoboCup 2006: Robot Soccer World Cup X, 2006

2005

Flexible Coordination of Multiagent Team Behavior Using HTN Planning.

[BibT_eX]

[DOI]

Proceedings of the RoboCup 2005: Robot Soccer World Cup IX, 2005

Getting closer: How Simulation and Humanoid League can benefit from each other.

[BibT_eX]

Masaki Ogino

Rodrigo da Silva Guerra

Masaaki Kikuchi