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ORCIDJoschka Boedecker
Joschka Bödecker
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- affiliation: University of Freiburg, Department of Computer Science, Germany
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2020 – today
- 2024
[j15]Ann-Kathrin Kiessner
, Robin Tibor Schirrmeister, Joschka Boedecker, Tonio Ball:
Reaching the ceiling? Empirical scaling behaviour for deep EEG pathology classification. Comput. Biol. Medicine 178: 108681 (2024)- [c43]Yuan Zhang, Jasper Hoffmann, Joschka Boedecker:
UDUC: An Uncertainty-Driven Approach for Learning-Based Robust Control. ECAI 2024: 4402-4409 - [c42]Yuan Zhang, Umashankar Deekshith, Jianhong Wang, Joschka Boedecker:
Improving the Efficiency and Efficacy of Multi-Agent Reinforcement Learning on Complex Railway Networks with a Local-Critic Approach. ICAPS 2024: 698-706 - [c41]Shengchao Yan, Baohe Zhang, Yuan Zhang, Joschka Boedecker, Wolfram Burgard:
Learning Continuous Control with Geometric Regularity from Robot Intrinsic Symmetry. ICRA 2024: 49-55 - [c40]Jasper Hoffmann, Diego Fernandez Clausen, Julien Brosseit, Julian Bernhard, Klemens Esterle, Moritz Werling, Michael Karg, Joschka Bödecker:
PlanNetX: Learning an efficient neural network planner from MPC for longitudinal control. L4DC 2024: 1214-1227 - [i50]Yannick Vogt, Mehdi Naouar, Maria Kalweit, Christoph Cornelius Miething, Justus Duyster, Roland Mertelsmann, Gabriel Kalweit, Joschka Boedecker:
Stable Online and Offline Reinforcement Learning for Antibody CDRH3 Design. CoRR abs/2401.05341 (2024) - [i49]Baohe Zhang, Yuan Zhang, Lilli Frison, Thomas Brox, Joschka Bödecker:
Constrained Reinforcement Learning with Smoothed Log Barrier Function. CoRR abs/2403.14508 (2024) - [i48]Mariella Dreissig, Florian Piewak, Joschka Boedecker:
Hierarchical Insights: Exploiting Structural Similarities for Reliable 3D Semantic Segmentation. CoRR abs/2404.06124 (2024) - [i47]Jasper Hoffmann, Diego Fernandez Clausen, Julien Brosseit, Julian Bernhard, Klemens Esterle, Moritz Werling, Michael Karg, Joschka Boedecker:
PlanNetX: Learning an Efficient Neural Network Planner from MPC for Longitudinal Control. CoRR abs/2404.18863 (2024) - [i46]Yuan Zhang, Jasper Hoffmann, Joschka Boedecker:
UDUC: An Uncertainty-driven Approach for Learning-based Robust Control. CoRR abs/2405.02598 (2024) - [i45]Yuan Zhang, Shaohui Yang, Toshiyuki Ohtsuka, Colin Jones, Joschka Boedecker:
Latent Linear Quadratic Regulator for Robotic Control Tasks. CoRR abs/2407.11107 (2024) - [i44]Jan Ole von Hartz, Tim Welschehold, Abhinav Valada, Joschka Boedecker:
The Art of Imitation: Learning Long-Horizon Manipulation Tasks from Few Demonstrations. CoRR abs/2407.13432 (2024) - [i43]Marieke Wesselkamp, Matthew Chantry, Ewan Pinnington, Margarita Choulga, Souhail Boussetta, Maria Kalweit, Joschka Boedecker, Carsten F. Dormann, Florian Pappenberger, Gianpaolo Balsamo:
Advances in Land Surface Model-based Forecasting: A comparative study of LSTM, Gradient Boosting, and Feedforward Neural Network Models as prognostic state emulators. CoRR abs/2407.16463 (2024) - [i42]David Eckel, Baohe Zhang, Joschka Bödecker:
Revisiting Safe Exploration in Safe Reinforcement learning. CoRR abs/2409.01245 (2024) - [i41]Yannick Vogt, Mehdi Naouar, Maria Kalweit, Christoph Cornelius Miething, Justus Duyster, Joschka Boedecker, Gabriel Kalweit:
BetterBodies: Reinforcement Learning guided Diffusion for Antibody Sequence Design. CoRR abs/2409.16298 (2024) - [i40]Baohe Zhang, Lilli Frison, Thomas Brox, Joschka Bödecker:
Constrained Reinforcement Learning for Safe Heat Pump Control. CoRR abs/2409.19716 (2024) - 2023
- [j14]Maria Kalweit, Andrea M. Burden, Joschka Boedecker, Thomas Hügle, Theresa Burkard:
Patient groups in Rheumatoid arthritis identified by deep learning respond differently to biologic or targeted synthetic DMARDs. PLoS Comput. Biol. 19(6) (2023) - [j13]Nicolai Dorka, Tim Welschehold, Joschka Bödecker, Wolfram Burgard:
Adaptively Calibrated Critic Estimates for Deep Reinforcement Learning. IEEE Robotics Autom. Lett. 8(2): 624-631 (2023) - [j12]Jan Ole von Hartz, Eugenio Chisari, Tim Welschehold, Wolfram Burgard, Joschka Boedecker, Abhinav Valada:
The Treachery of Images: Bayesian Scene Keypoints for Deep Policy Learning in Robotic Manipulation. IEEE Robotics Autom. Lett. 8(11): 6931-6938 (2023) - [c39]Andrea Ghezzi, Jasper Hoffmann, Jonathan Frey, Joschka Boedecker, Moritz Diehl:
Imitation Learning from Nonlinear MPC via the Exact Q-Loss and its Gauss-Newton Approximation. CDC 2023: 4766-4771 - [c38]Yuan Zhang, Jianhong Wang, Joschka Boedecker:
Robust Reinforcement Learning in Continuous Control Tasks with Uncertainty Set Regularization. CoRL 2023: 1400-1424 - [c37]Suresh Guttikonda, Jan Achterhold, Haolong Li, Joschka Boedecker, Joerg Stueckler:
Context-Conditional Navigation with a Learning-Based Terrain- and Robot-Aware Dynamics Model. ECMR 2023: 1-7 - [c36]Rudolf Reiter, Jasper Hoffmann, Joschka Boedecker, Moritz Diehl:
A Hierarchical Approach for Strategic Motion Planning in Autonomous Racing. ECC 2023: 1-8 - [c35]Mariella Dreissig, Florian Piewak, Joschka Boedecker:
On the Calibration of Uncertainty Estimation in LiDAR-Based Semantic Segmentation. ITSC 2023: 4798-4805 - [c34]Mariella Dreissig, Dominik Scheuble, Florian Piewak, Joschka Boedecker:
Survey on LiDAR Perception in Adverse Weather Conditions. IV 2023: 1-8 - [i39]Yuan Zhang, Joschka Boedecker, Chuxuan Li, Guyue Zhou:
Incorporating Recurrent Reinforcement Learning into Model Predictive Control for Adaptive Control in Autonomous Driving. CoRR abs/2301.13313 (2023) - [i38]Mehdi Naouar, Gabriel Kalweit, Ignacio Mastroleo, Philipp Poxleitner, Marc Christian Metzger, Joschka Boedecker, Maria Kalweit:
Robust Tumor Detection from Coarse Annotations via Multi-Magnification Ensembles. CoRR abs/2303.16533 (2023) - [i37]Andrea Ghezzi, Jasper Hoffmann, Jonathan Frey, Joschka Boedecker, Moritz Diehl:
Imitation Learning from Nonlinear MPC via the Exact Q-Loss and its Gauss-Newton Approximation. CoRR abs/2304.01782 (2023) - [i36]Mariella Dreissig, Dominik Scheuble, Florian Piewak, Joschka Boedecker:
Survey on LiDAR Perception in Adverse Weather Conditions. CoRR abs/2304.06312 (2023) - [i35]Jan Ole von Hartz, Eugenio Chisari, Tim Welschehold, Wolfram Burgard, Joschka Boedecker, Abhinav Valada:
The Treachery of Images: Bayesian Scene Keypoints for Deep Policy Learning in Robotic Manipulation. CoRR abs/2305.04718 (2023) - [i34]Shengchao Yan, Yuan Zhang, Baohe Zhang, Joschka Boedecker, Wolfram Burgard:
Geometric Regularity with Robot Intrinsic Symmetry in Reinforcement Learning. CoRR abs/2306.16316 (2023) - [i33]Suresh Guttikonda, Jan Achterhold, Haolong Li, Joschka Boedecker, Joerg Stueckler:
Context-Conditional Navigation with a Learning-Based Terrain- and Robot-Aware Dynamics Model. CoRR abs/2307.09206 (2023) - [i32]Mariella Dreissig, Florian Piewak, Joschka Boedecker:
On the Calibration of Uncertainty Estimation in LiDAR-based Semantic Segmentation. CoRR abs/2308.02248 (2023) - [i31]Lukas Alexander Wilhelm Gemein, Robin Tibor Schirrmeister, Joschka Boedecker, Tonio Ball:
Brain Age Revisited: Investigating the State vs. Trait Hypotheses of EEG-derived Brain-Age Dynamics with Deep Learning. CoRR abs/2310.07029 (2023) - [i30]Hao Zhu, Brice De La Crompe, Gabriel Kalweit, Artur Schneider, Maria Kalweit, Ilka Diester, Joschka Boedecker:
L(M)V-IQL: Multiple Intention Inverse Reinforcement Learning for Animal Behavior Characterization. CoRR abs/2311.13870 (2023) - [i29]Mehdi Naouar, Gabriel Kalweit, Anusha Klett, Yannick Vogt, Paula Silvestrini, Diana Laura Infante Ramírez, Roland Mertelsmann, Joschka Boedecker, Maria Kalweit:
CellMixer: Annotation-free Semantic Cell Segmentation of Heterogeneous Cell Populations. CoRR abs/2312.00671 (2023) - 2022
- [j11]Eugenio Chisari, Tim Welschehold, Joschka Boedecker, Wolfram Burgard, Abhinav Valada:
Correct Me If I am Wrong: Interactive Learning for Robotic Manipulation. IEEE Robotics Autom. Lett. 7(2): 3695-3702 (2022) - [j10]Gabriel Kalweit, Maria Kalweit, Joschka Boedecker:
Robust and Data-efficient Q-learning by Composite Value-estimation. Trans. Mach. Learn. Res. 2022 (2022) - [c33]Erick Rosete-Beas, Oier Mees, Gabriel Kalweit, Joschka Boedecker, Wolfram Burgard:
Latent Plans for Task-Agnostic Offline Reinforcement Learning. CoRL 2022: 1838-1849 - [c32]Maria Kalweit, Gabriel Kalweit, Moritz Werling, Joschka Boedecker:
Deep Surrogate Q-Learning for Autonomous Driving. ICRA 2022: 1578-1584 - [c31]Jessica Borja-Diaz, Oier Mees, Gabriel Kalweit, Lukás Hermann, Joschka Boedecker, Wolfram Burgard:
Affordance Learning from Play for Sample-Efficient Policy Learning. ICRA 2022: 6372-6378 - [i28]Jessica Borja-Diaz, Oier Mees, Gabriel Kalweit, Lukás Hermann, Joschka Boedecker, Wolfram Burgard:
Affordance Learning from Play for Sample-Efficient Policy Learning. CoRR abs/2203.00352 (2022) - [i27]Branka Mirchevska, Moritz Werling, Joschka Boedecker:
Optimizing Trajectories for Highway Driving with Offline Reinforcement Learning. CoRR abs/2203.10949 (2022) - [i26]Yuan Zhang, Jianhong Wang, Joschka Boedecker:
Robust Reinforcement Learning in Continuous Control Tasks with Uncertainty Set Regularization. CoRR abs/2207.02016 (2022) - [i25]Erick Rosete-Beas, Oier Mees, Gabriel Kalweit, Joschka Boedecker, Wolfram Burgard:
Latent Plans for Task-Agnostic Offline Reinforcement Learning. CoRR abs/2209.08959 (2022) - [i24]Mariella Dreissig, Florian Piewak, Joschka Boedecker:
On the calibration of underrepresented classes in LiDAR-based semantic segmentation. CoRR abs/2210.06811 (2022) - [i23]Rudolf Reiter, Jasper Hoffmann, Joschka Boedecker, Moritz Diehl:
A Hierarchical Approach for Strategic Motion Planning in Autonomous Racing. CoRR abs/2212.01607 (2022) - 2021
- [c30]Branka Mirchevska, Maria Hügle, Gabriel Kalweit, Moritz Werling, Joschka Boedecker:
Amortized Q-learning with Model-based Action Proposals for Autonomous Driving on Highways. ICRA 2021: 1028-1035 - [c29]Maria Kalweit, Gabriel Kalweit, Joschka Boedecker:
AnyNets: Adaptive Deep Neural Networks for Medical Data with Missing Values. AI4Function@IJCAI 2021: 12-21 - [c28]Alireza Ranjbar, Ngo Anh Vien, Hanna Ziesche, Joschka Boedecker, Gerhard Neumann:
Residual Feedback Learning for Contact-Rich Manipulation Tasks with Uncertainty. IROS 2021: 2383-2390 - [c27]Gabriel Kalweit, Maria Hügle, Moritz Werling, Joschka Boedecker:
Q-learning with Long-term Action-space Shaping to Model Complex Behavior for Autonomous Lane Changes. IROS 2021: 5641-5648 - [i22]Alireza Ranjbar, Ngo Anh Vien, Hanna Ziesche, Joschka Boedecker, Gerhard Neumann:
Residual Feedback Learning for Contact-Rich Manipulation Tasks with Uncertainty. CoRR abs/2106.04306 (2021) - [i21]Eugenio Chisari, Tim Welschehold, Joschka Boedecker, Wolfram Burgard, Abhinav Valada:
Correct Me if I am Wrong: Interactive Learning for Robotic Manipulation. CoRR abs/2110.03316 (2021) - [i20]Nicolai Dorka, Joschka Boedecker, Wolfram Burgard:
Adaptively Calibrated Critic Estimates for Deep Reinforcement Learning. CoRR abs/2111.12673 (2021) - 2020
- [j9]Lukas Alexander Wilhelm Gemein, Robin Tibor Schirrmeister, Patryk Chrabaszcz, Daniel Wilson, Joschka Boedecker, Andreas Schulze-Bonhage, Frank Hutter, Tonio Ball:
Machine-learning-based diagnostics of EEG pathology. NeuroImage 220: 117021 (2020) - [c26]Maria Hügle, Gabriel Kalweit, Moritz Werling, Joschka Boedecker:
Dynamic Interaction-Aware Scene Understanding for Reinforcement Learning in Autonomous Driving. ICRA 2020: 4329-4335 - [c25]Marina Kollmitz, Torsten Koller, Joschka Boedecker, Wolfram Burgard:
Learning Human-Aware Robot Navigation from Physical Interaction via Inverse Reinforcement Learning. IROS 2020: 11025-11031 - [c24]Gabriel Kalweit, Maria Hügle, Moritz Werling, Joschka Boedecker:
Deep Inverse Q-learning with Constraints. NeurIPS 2020 - [i19]Lukas Alexander Wilhelm Gemein, Robin Tibor Schirrmeister, Patryk Chrabaszcz, Daniel Wilson, Joschka Boedecker, Andreas Schulze-Bonhage, Frank Hutter, Tonio Ball:
Machine-Learning-Based Diagnostics of EEG Pathology. CoRR abs/2002.05115 (2020) - [i18]Gabriel Kalweit, Maria Hügle, Moritz Werling, Joschka Boedecker:
Interpretable Multi Time-scale Constraints in Model-free Deep Reinforcement Learning for Autonomous Driving. CoRR abs/2003.09398 (2020) - [i17]Gabriel Kalweit, Maria Hügle, Moritz Werling, Joschka Boedecker:
Deep Inverse Q-learning with Constraints. CoRR abs/2008.01712 (2020) - [i16]Maria Hügle, Gabriel Kalweit, Thomas Huegle, Joschka Boedecker:
A Dynamic Deep Neural Network For Multimodal Clinical Data Analysis. CoRR abs/2008.06294 (2020) - [i15]Maria Kalweit, Gabriel Kalweit, Moritz Werling, Joschka Boedecker:
Deep Surrogate Q-Learning for Autonomous Driving. CoRR abs/2010.11278 (2020) - [i14]Branka Mirchevska, Maria Hügle, Gabriel Kalweit, Moritz Werling, Joschka Boedecker:
Amortized Q-learning with Model-based Action Proposals for Autonomous Driving on Highways. CoRR abs/2012.03234 (2020)
2010 – 2019
- 2019
- [j8]Lukas Dominique Josef Fiederer, Martin Völker, Robin Tibor Schirrmeister, Wolfram Burgard, Joschka Boedecker, Tonio Ball:
Hybrid Brain-Computer-Interfacing for Human-Compliant Robots: Inferring Continuous Subjective Ratings With Deep Regression. Frontiers Neurorobotics 13: 76 (2019) - [j7]Jan M. Wülfing, Sreedhar S. Kumar, Joschka Boedecker, Martin A. Riedmiller, Ulrich Egert:
Adaptive long-term control of biological neural networks with Deep Reinforcement Learning. Neurocomputing 342: 66-74 (2019) - [j6]Jingwei Zhang, Lei Tai, Peng Yun, Yufeng Xiong, Ming Liu, Joschka Boedecker, Wolfram Burgard:
VR-Goggles for Robots: Real-to-Sim Domain Adaptation for Visual Control. IEEE Robotics Autom. Lett. 4(2): 1148-1155 (2019) - [j5]Daniel Kuhner, Lukas Dominique Josef Fiederer, Johannes Aldinger, Felix Burget, Martin Völker, Robin Tibor Schirrmeister, Chau Do, Joschka Boedecker, Bernhard Nebel, Tonio Ball, Wolfram Burgard:
A service assistant combining autonomous robotics, flexible goal formulation, and deep-learning-based brain-computer interfacing. Robotics Auton. Syst. 116: 98-113 (2019) - [c23]Mohamed Abou-Hussein, Stefan H. Müller, Joschka Boedecker:
Multimodal Spatio-Temporal Information in End-to-End Networks for Automotive Steering Prediction. ICRA 2019: 8641-8647 - [c22]Maria Hügle, Gabriel Kalweit, Branka Mirchevska, Moritz Werling, Joschka Boedecker:
Dynamic Input for Deep Reinforcement Learning in Autonomous Driving. IROS 2019: 7566-7573 - [i13]Jingwei Zhang, Niklas Wetzel, Nicolai Dorka, Joschka Boedecker, Wolfram Burgard:
Scheduled Intrinsic Drive: A Hierarchical Take on Intrinsically Motivated Exploration. CoRR abs/1903.07400 (2019) - [i12]Torsten Koller, Felix Berkenkamp, Matteo Turchetta, Joschka Boedecker, Andreas Krause:
Learning-based Model Predictive Control for Safe Exploration and Reinforcement Learning. CoRR abs/1906.12189 (2019) - [i11]Maria Hügle, Gabriel Kalweit, Branka Mirchevska, Moritz Werling, Joschka Boedecker:
Dynamic Input for Deep Reinforcement Learning in Autonomous Driving. CoRR abs/1907.10994 (2019) - [i10]Gabriel Kalweit, Maria Hügle, Joschka Boedecker:
Off-policy Multi-step Q-learning. CoRR abs/1909.13518 (2019) - [i9]Maria Hügle, Gabriel Kalweit, Moritz Werling, Joschka Boedecker:
Dynamic Interaction-Aware Scene Understanding for Reinforcement Learning in Autonomous Driving. CoRR abs/1909.13582 (2019) - 2018
- [c21]Simon Heller, Maria Hügle, Iman Nematollahi, Farrokh Manzouri, Matthias Dümpelmann, Andreas Schulze-Bonhage, Joschka Boedecker, Peter Woias:
Hardware Implementation of a Performance and Energy-optimized Convolutional Neural Network for Seizure Detection. EMBC 2018: 2268-2271 - [c20]Jan Wülfing, Sreedhar S. Kumar, Joschka Boedecker, Martin A. Riedmiller, Ulrich Egert:
Controlling biological neural networks with deep reinforcement learning. ESANN 2018 - [c19]Robert Dürichen, Keshav Deep Verma, Seow Yuen Yee, Thomas Rocznik, Philip Schmidt, Joschka Boedecker, Christian Peters:
Prediction of electrocardiography features points using seismocardiography data: a machine learning approach. UbiComp 2018: 96-99 - [c18]Maria Hügle, Simon Heller, Manuel Watter, Manuel Blum, Farrokh Manzouri, Matthias Dümpelmann, Andreas Schulze-Bonhage, Peter Woias, Joschka Boedecker:
Early Seizure Detection with an Energy-Efficient Convolutional Neural Network on an Implantable Microcontroller. IJCNN 2018: 1-7 - [c17]Branka Mirchevska, Christian Pek, Moritz Werling, Matthias Althoff, Joschka Boedecker:
High-level Decision Making for Safe and Reasonable Autonomous Lane Changing using Reinforcement Learning. ITSC 2018: 2156-2162 - [i8]Jingwei Zhang, Lei Tai, Yufeng Xiong, Ming Liu, Joschka Boedecker, Wolfram Burgard:
VR Goggles for Robots: Real-to-sim Domain Adaptation for Visual Control. CoRR abs/1802.00265 (2018) - [i7]Maria Hügle, Simon Heller, Manuel Watter, Manuel Blum, Farrokh Manzouri, Matthias Dümpelmann, Andreas Schulze-Bonhage, Peter Woias, Joschka Boedecker:
Early Seizure Detection with an Energy-Efficient Convolutional Neural Network on an Implantable Microcontroller. CoRR abs/1806.04549 (2018) - 2017
- [c16]Gabriel Kalweit, Joschka Boedecker:
Uncertainty-driven Imagination for Continuous Deep Reinforcement Learning. CoRL 2017: 195-206 - [c15]Felix Burget, Lukas Dominique Josef Fiederer, Daniel Kuhner, Martin Völker, Johannes Aldinger, Robin Tibor Schirrmeister, Chau Do, Joschka Boedecker, Bernhard Nebel, Tonio Ball, Wolfram Burgard:
Acting thoughts: Towards a mobile robotic service assistant for users with limited communication skills. ECMR 2017: 1-6 - [c14]Wolfgang Groß, Sascha Lange, Joschka Bödecker, Manuel Blum:
Predicting Time Series with Space-Time Convolutional and Recurrent Neural Networks. ESANN 2017 - [c13]Jingwei Zhang, Jost Tobias Springenberg, Joschka Boedecker, Wolfram Burgard:
Deep reinforcement learning with successor features for navigation across similar environments. IROS 2017: 2371-2378 - [i6]Jingwei Zhang, Lei Tai, Joschka Boedecker, Wolfram Burgard, Ming Liu:
Neural SLAM. CoRR abs/1706.09520 (2017) - [i5]Felix Burget, Lukas Dominique Josef Fiederer, Daniel Kuhner, Martin Voelker, Johannes Aldinger, Robin Tibor Schirrmeister, Chau Do, Joschka Boedecker, Bernhard Nebel, Tonio Ball, Wolfram Burgard:
Acting Thoughts: Towards a Mobile Robotic Service Assistant for Users with Limited Communication Skills. CoRR abs/1707.06633 (2017) - 2016
- [j4]Sreedhar S. Kumar, Jan Wülfing, Samora Okujeni, Joschka Boedecker, Martin A. Riedmiller, Ulrich Egert:
Autonomous Optimization of Targeted Stimulation of Neuronal Networks. PLoS Comput. Biol. 12(8) (2016) - [i4]Jingwei Zhang, Jost Tobias Springenberg, Joschka Boedecker, Wolfram Burgard:
Deep Reinforcement Learning with Successor Features for Navigation across Similar Environments. CoRR abs/1612.05533 (2016) - 2015
- [j3]Wendelin Böhmer, Jost Tobias Springenberg, Joschka Boedecker, Martin A. Riedmiller, Klaus Obermayer:
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. Künstliche Intell. 29(4): 353-362 (2015) - [c12]Manuel Watter, Jost Tobias Springenberg, Joschka Boedecker, Martin A. Riedmiller:
Embed to Control: A Locally Linear Latent Dynamics Model for Control from Raw Images. NIPS 2015: 2746-2754 - [i3]Manuel Watter, Jost Tobias Springenberg, Joschka Boedecker, Martin A. Riedmiller:
Embed to Control: A Locally Linear Latent Dynamics Model for Control from Raw Images. CoRR abs/1506.07365 (2015) - 2014
- [c11]Joschka Boedecker, Jost Tobias Springenberg, Jan Wülfing, Martin A. Riedmiller:
Approximate real-time optimal control based on sparse Gaussian process models. ADPRL 2014: 1-8 - 2013
- [i2]Oliver Obst, Joschka Boedecker, Benedikt Schmidt, Minoru Asada:
On active information storage in input-driven systems. CoRR abs/1303.5526 (2013) - [i1]Oliver Obst, Joschka Boedecker:
Guided Self-Organization of Input-Driven Recurrent Neural Networks. CoRR abs/1309.1524 (2013) - 2012
- [j2]Joschka Boedecker, Oliver Obst, Joseph T. Lizier, Norbert Michael Mayer, Minoru Asada:
Information processing in echo state networks at the edge of chaos. Theory Biosci. 131(3): 205-213 (2012) - [c10]Christoph Hartmann, Joschka Boedecker, Oliver Obst, Shuhei Ikemoto, Minoru Asada:
Real-Time Inverse Dynamics Learning for Musculoskeletal Robots based on Echo State Gaussian Process Regression. Robotics: Science and Systems 2012 - 2011
- [c9]Beata J. Grzyb, Joschka Boedecker, Minoru Asada, Angel P. del Pobil, Linda B. Smith:
Between Frustration and Elation: Sense of Control Regulates the lntrinsic Motivation for Motor Learning. Lifelong Learning 2011 - [c8]Beata J. Grzyb, Joschka Boedecker, Minoru Asada, Angel P. del Pobil, Linda B. Smith:
Trying anyways: How ignoring the errors may help in learning new skills. ICDL-EPIROB 2011: 1-6 - 2010
- [c7]Oliver Obst, Joschka Boedecker, Minoru Asada:
Improving Recurrent Neural Network Performance Using Transfer Entropy. ICONIP (2) 2010: 193-200
2000 – 2009
- 2009
- [j1]Norbert Michael Mayer, Joschka Boedecker, Minoru Asada:
Robot motion description and real-time management with the Harmonic Motion Description Protocol. Robotics Auton. Syst. 57(8): 870-876 (2009) - [c6]Joschka Boedecker, Oliver Obst, Norbert Michael Mayer, Minoru Asada:
Studies on reservoir initialization and dynamics shaping in echo state networks. ESANN 2009 - 2007
- [c5]Norbert Michael Mayer, Joschka Boedecker, Kazuhiro Masui, Masaki Ogino, Minoru Asada:
HMDP: A New Protocol for Motion Pattern Generation Towards Behavior Abstraction. RoboCup 2007: 184-195 - [c4]Rodrigo da Silva Guerra, Joschka Boedecker, Norbert Michael Mayer, Shinzo Yanagimachi, Yasuji Hirosawa, Kazuhiko Yoshikawa, Masaaki Namekawa, Minoru Asada:
Introducing Physical Visualization Sub-league. RoboCup 2007: 496-503 - 2006
- [c3]Norbert Michael Mayer, Joschka Boedecker, Rodrigo da Silva Guerra, Oliver Obst, Minoru Asada:
3D2Real: Simulation League Finals in Real Robots. RoboCup 2006: 25-34 - 2005
- [c2]Joschka Boedecker, Norbert Michael Mayer, Masaki Ogino, Rodrigo da Silva Guerra, Masaaki Kikuchi, Minoru Asada:
Getting closer: How Simulation and Humanoid League can benefit from each other. AMiRE 2005: 93-98 - [c1]Oliver Obst, Joschka Boedecker:
Flexible Coordination of Multiagent Team Behavior Using HTN Planning. RoboCup 2005: 521-528
Coauthor Index
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