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ORCIDGerhard Neumann
Person information
- affiliation: Karlsruhe Institute of Technology, Institute for Anthropomatics and Robotics, Germany
- affiliation: University of Lincoln, Center for Autonomous Systems (L-CAS), UK
- affiliation (former): TU Darmstadt, Department of Computer Science, Germany
- affiliation (PhD 2012): Graz University of Technology, Austria
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2020 – today
- 2024
[j53]Philipp Becker, Sebastian Mossburger, Fabian Otto, Gerhard Neumann:
Combining Reconstruction and Contrastive Methods for Multimodal Representations in RL. RLJ 4: 1619-1655 (2024)- [j52]Manuel Zaremski, Blanca Handwerker, Christian R. G. Dreher, Fabian Leven, David Schneider, Alina Roitberg, Rainer Stiefelhagen, Gerhard Neumann, Michael Heizmann, Tamim Asfour, Barbara Deml:
Learning human actions from complex manipulation tasks and their transfer to robots in the circular factory. Autom. 72(9): 844-860 (2024) - [j51]Jürgen Fleischer, Frederik Zanger, Volker Schulze, Gerhard Neumann, Nicole Stricker, Kai Furmans, Julius Pfrommer, Gisela Lanza, Malte Hansjosten, Patrick Fischmann, Julia Dvorak, Jan-Felix Klein, Felix Rauscher, Andreas Ebner, Marvin Carl May, Philipp Gönnheimer:
Self-learning and autonomously adapting manufacturing equipment for the circular factory. Autom. 72(9): 861-874 (2024) - [j50]Constantin Hofmann, Steffen Staab, Michael Selzer, Gerhard Neumann, Kai Furmans, Michael Heizmann, Jürgen Beyerer, Gisela Lanza, Julius Pfrommer, Tobias Düser, Jan-Felix Klein:
The role of an ontology-based knowledge backbone in a circular factory. Autom. 72(9): 875-883 (2024) - [j49]Maximilian Hüttenrauch, Gerhard Neumann:
Robust Black-Box Optimization for Stochastic Search and Episodic Reinforcement Learning. J. Mach. Learn. Res. 25: 153:1-153:44 (2024) - [j48]Paul Maria Scheikl
, Nicolas Schreiber, Christoph Haas, Niklas Freymuth, Gerhard Neumann, Rudolf Lioutikov, Franziska Mathis-Ullrich:
Movement Primitive Diffusion: Learning Gentle Robotic Manipulation of Deformable Objects. IEEE Robotics Autom. Lett. 9(6): 5338-5345 (2024) - [c121]Benjamin Alt, Urs Keßner, Aleksandar Taranovic, Darko Katic, Andreas Hermann, Rainer Jäkel, Gerhard Neumann:
Domain-Specific Fine-Tuning of Large Language Models for Interactive Robot Programming. ERF (1) 2024: 274-279 - [c120]Xinkai Jiang, Paul Mattes, Xiaogang Jia, Nicolas Schreiber, Gerhard Neumann, Rudolf Lioutikov:
A Comprehensive User Study on Augmented Reality-Based Data Collection Interfaces for Robot Learning. HRI 2024: 333-342 - [c119]Hadi Beik-Mohammadi, Søren Hauberg, Georgios Arvanitidis, Nadia Figueroa, Gerhard Neumann, Leonel Rozo:
Neural Contractive Dynamical Systems. ICLR 2024 - [c118]Xiaogang Jia, Denis Blessing, Xinkai Jiang, Moritz Reuss, Atalay Donat, Rudolf Lioutikov, Gerhard Neumann:
Towards Diverse Behaviors: A Benchmark for Imitation Learning with Human Demonstrations. ICLR 2024 - [c117]Ge Li, Hongyi Zhou, Dominik Roth, Serge Thilges, Fabian Otto, Rudolf Lioutikov, Gerhard Neumann:
Open the Black Box: Step-based Policy Updates for Temporally-Correlated Episodic Reinforcement Learning. ICLR 2024 - [c116]Denis Blessing, Xiaogang Jia, Johannes Esslinger, Francisco Vargas, Gerhard Neumann:
Beyond ELBOs: A Large-Scale Evaluation of Variational Methods for Sampling. ICML 2024 - [c115]Onur Celik, Aleksandar Taranovic, Gerhard Neumann:
Acquiring Diverse Skills using Curriculum Reinforcement Learning with Mixture of Experts. ICML 2024 - [c114]Rebekka Charlotte Peter, Steffen Peikert, Ludwig Haide, Doan Xuan Viet Pham, Tahar Chettaoui, Eleonora Tagliabue, Paul Maria Scheikl, Johannes Fauser, Matthias Hillenbrand, Gerhard Neumann, Franziska Mathis-Ullrich:
Lens Capsule Tearing in Cataract Surgery using Reinforcement Learning. ICRA 2024: 15501-15508 - [c113]Claudius Kienle, Benjamin Alt, Onur Celik, Philipp Becker, Darko Katic, Rainer Jäkel, Gerhard Neumann:
MuTT: A Multimodal Trajectory Transformer for Robot Skills. IROS 2024: 9644-9651 - [c112]Puze Liu, Jonas Günster, Niklas Funk, Simon Gröger, Dong Chen, Haitham Bou-Ammar, Julius Jankowski, Ante Maric, Sylvain Calinon, Andrej Orsula, Miguel S. Olivares-Méndez, Hongyi Zhou, Rudolf Lioutikov, Gerhard Neumann, Amarildo Likmeta, Amirhossein Zhalehmehrabi, Thomas Bonenfant, Marcello Restelli, Davide Tateo, Ziyuan Liu, Jan R. Peters:
A Retrospective on the Robot Air Hockey Challenge: Benchmarking Robust, Reliable, and Safe Learning Techniques for Real-world Robotics. NeurIPS 2024 - [c111]Hongyi Zhou, Denis Blessing, Ge Li, Onur Celik, Xiaogang Jia, Gerhard Neumann, Rudolf Lioutikov:
Variational Distillation of Diffusion Policies into Mixture of Experts. NeurIPS 2024 - [c110]Pit Henrich, Balázs Gyenes, Paul Maria Scheikl, Gerhard Neumann, Franziska Mathis-Ullrich:
Registered and Segmented Deformable Object Reconstruction from a Single View Point Cloud. WACV 2024: 3117-3126 - [i85]Hadi Beik-Mohammadi, Søren Hauberg, Georgios Arvanitidis, Nadia Figueroa, Gerhard Neumann, Leonel Rozo:
Neural Contractive Dynamical Systems. CoRR abs/2401.09352 (2024) - [i84]Ge Li, Hongyi Zhou, Dominik Roth, Serge Thilges, Fabian Otto, Rudolf Lioutikov, Gerhard Neumann:
Open the Black Box: Step-based Policy Updates for Temporally-Correlated Episodic Reinforcement Learning. CoRR abs/2401.11437 (2024) - [i83]Tobias Würth, Niklas Freymuth, Clemens Zimmerling, Gerhard Neumann, Luise Kärger:
Physics-informed MeshGraphNets (PI-MGNs): Neural finite element solvers for non-stationary and nonlinear simulations on arbitrary meshes. CoRR abs/2402.10681 (2024) - [i82]Xiaogang Jia, Denis Blessing, Xinkai Jiang, Moritz Reuss, Atalay Donat, Rudolf Lioutikov, Gerhard Neumann:
Towards Diverse Behaviors: A Benchmark for Imitation Learning with Human Demonstrations. CoRR abs/2402.14606 (2024) - [i81]Fabian Otto, Philipp Becker, Ngo Anh Vien, Gerhard Neumann:
Vlearn: Off-Policy Learning with Efficient State-Value Function Estimation. CoRR abs/2403.04453 (2024) - [i80]Onur Celik, Aleksandar Taranovic, Gerhard Neumann:
Acquiring Diverse Skills using Curriculum Reinforcement Learning with Mixture of Experts. CoRR abs/2403.06966 (2024) - [i79]Denis Blessing, Xiaogang Jia, Johannes Esslinger, Francisco Vargas, Gerhard Neumann:
Beyond ELBOs: A Large-Scale Evaluation of Variational Methods for Sampling. CoRR abs/2406.07423 (2024) - [i78]Xiaogang Jia, Qian Wang, Atalay Donat, Bowen Xing, Ge Li, Hongyi Zhou, Onur Celik, Denis Blessing, Rudolf Lioutikov, Gerhard Neumann:
MaIL: Improving Imitation Learning with Mamba. CoRR abs/2406.08234 (2024) - [i77]Niklas Freymuth, Philipp Dahlinger, Tobias Würth, Simon Reisch, Luise Kärger, Gerhard Neumann:
Adaptive Swarm Mesh Refinement using Deep Reinforcement Learning with Local Rewards. CoRR abs/2406.08440 (2024) - [i76]Hongyi Zhou, Denis Blessing, Ge Li, Onur Celik, Xiaogang Jia, Gerhard Neumann, Rudolf Lioutikov:
Variational Distillation of Diffusion Policies into Mixture of Experts. CoRR abs/2406.12538 (2024) - [i75]Niklas Freymuth, Philipp Dahlinger, Tobias Würth, Philipp Becker, Aleksandar Taranovic, Onno Grönheim, Luise Kärger, Gerhard Neumann:
Iterative Sizing Field Prediction for Adaptive Mesh Generation From Expert Demonstrations. CoRR abs/2406.14161 (2024) - [i74]Philipp Becker, Niklas Freymuth, Gerhard Neumann:
KalMamba: Towards Efficient Probabilistic State Space Models for RL under Uncertainty. CoRR abs/2406.15131 (2024) - [i73]Claudius Kienle, Benjamin Alt, Onur Celik, Philipp Becker, Darko Katic, Rainer Jäkel, Gerhard Neumann:
MuTT: A Multimodal Trajectory Transformer for Robot Skills. CoRR abs/2407.15660 (2024) - [i72]Ge Li, Dong Tian, Hongyi Zhou, Xinkai Jiang, Rudolf Lioutikov, Gerhard Neumann:
TOP-ERL: Transformer-based Off-Policy Episodic Reinforcement Learning. CoRR abs/2410.09536 (2024) - [i71]Andreas Boltres, Niklas Freymuth, Patrick Jahnke, Holger Karl, Gerhard Neumann:
Learning Sub-Second Routing Optimization in Computer Networks requires Packet-Level Dynamics. CoRR abs/2410.10377 (2024) - [i70]Balázs Gyenes, Nikolai Franke, Philipp Becker, Gerhard Neumann:
PointPatchRL - Masked Reconstruction Improves Reinforcement Learning on Point Clouds. CoRR abs/2410.18800 (2024) - [i69]Roman Freiberg, Alexander Qualmann, Ngo Anh Vien, Gerhard Neumann:
Diffusion for Multi-Embodiment Grasping. CoRR abs/2410.18835 (2024) - [i68]Emiliyan Gospodinov, Vaisakh Shaj, Philipp Becker, Stefan Geyer, Gerhard Neumann:
Adaptive World Models: Learning Behaviors by Latent Imagination Under Non-Stationarity. CoRR abs/2411.01342 (2024) - [i67]Puze Liu, Jonas Guenster, Niklas Funk, Simon Gröger, Dong Chen, Haitham Bou-Ammar, Julius Jankowski, Ante Maric, Sylvain Calinon, Andrej Orsula, Miguel S. Olivares-Méndez, Hongyi Zhou, Rudolf Lioutikov, Gerhard Neumann, Amarildo Likmeta, Amirhossein Zhalehmehrabi, Thomas Bonenfant, Marcello Restelli, Davide Tateo, Ziyuan Liu, Jan Peters:
A Retrospective on the Robot Air Hockey Challenge: Benchmarking Robust, Reliable, and Safe Learning Techniques for Real-world Robotics. CoRR abs/2411.05718 (2024) - [i66]Weiran Liao, Ge Li, Hongyi Zhou, Rudolf Lioutikov, Gerhard Neumann:
BMP: Bridging the Gap between B-Spline and Movement Primitives. CoRR abs/2411.10336 (2024) - [i65]Hadi Beik-Mohammadi, Søren Hauberg, Georgios Arvanitidis, Gerhard Neumann, Leonel Rozo:
Extended Neural Contractive Dynamical Systems: On Multiple Tasks and Riemannian Safety Regions. CoRR abs/2411.11405 (2024) - [i64]Huy Le, Miroslav Gabriel, Tai Hoang, Gerhard Neumann, Ngo Anh Vien:
Enhancing Exploration with Diffusion Policies in Hybrid Off-Policy RL: Application to Non-Prehensile Manipulation. CoRR abs/2411.14913 (2024) - [i63]Junhua Chen, Lorenz Richter, Julius Berner, Denis Blessing, Gerhard Neumann, Anima Anandkumar:
Sequential Controlled Langevin Diffusions. CoRR abs/2412.07081 (2024) - 2023
- [j47]Jairo Inga, Miriam Ruess, Jan Heinrich Robens, Thomas Nelius, Simon Rothfuß, Sean Kille, Philipp Dahlinger, Andreas Lindenmann, Roland Thomaschke, Gerhard Neumann, Sven Matthiesen, Sören Hohmann, Andrea Kiesel:
Human-machine symbiosis: A multivariate perspective for physically coupled human-machine systems. Int. J. Hum. Comput. Stud. 170: 102926 (2023) - [j46]Hadi Beik-Mohammadi, Søren Hauberg, Georgios Arvanitidis, Gerhard Neumann, Leonel Rozo:
Reactive motion generation on learned Riemannian manifolds. Int. J. Robotics Res. 42(10): 729-754 (2023) - [j45]Paul Maria Scheikl, Balázs Gyenes, Rayan Younis, Christoph Haas, Gerhard Neumann, Martin Wagner, Franziska Mathis-Ullrich:
LapGym - An Open Source Framework for Reinforcement Learning in Robot-Assisted Laparoscopic Surgery. J. Mach. Learn. Res. 24: 368:1-368:42 (2023) - [j44]Ge Li, Zeqi Jin, Michael Volpp, Fabian Otto, Rudolf Lioutikov, Gerhard Neumann:
ProDMP: A Unified Perspective on Dynamic and Probabilistic Movement Primitives. IEEE Robotics Autom. Lett. 8(4): 2325-2332 (2023) - [j43]Fabian Duffhauss, Sebastian Koch, Hanna Ziesche, Ngo Anh Vien, Gerhard Neumann:
SyMFM6D: Symmetry-Aware Multi-Directional Fusion for Multi-View 6D Object Pose Estimation. IEEE Robotics Autom. Lett. 8(9): 5315-5322 (2023) - [j42]Oleg Arenz, Philipp Dahlinger, Zihan Ye, Michael Volpp, Gerhard Neumann:
A Unified Perspective on Natural Gradient Variational Inference with Gaussian Mixture Models. Trans. Mach. Learn. Res. 2023 (2023) - [c109]Ning Gao, Bernard Hohmann, Gerhard Neumann:
Enhancing Interpretable Object Abstraction via Clustering-based Slot Initialization. BMVC 2023: 471-477 - [c108]Ning Gao, Ngo Anh Vien, Hanna Ziesche, Gerhard Neumann:
SA6D: Self-Adaptive Few-Shot 6D Pose Estimator for Novel and Occluded Objects. CoRL 2023: 1572-1595 - [c107]Jonas Linkerhägner, Niklas Freymuth, Paul Maria Scheikl, Franziska Mathis-Ullrich, Gerhard Neumann:
Grounding Graph Network Simulators using Physical Sensor Observations. ICLR 2023 - [c106]Aleksandar Taranovic, Andras Gabor Kupcsik, Niklas Freymuth, Gerhard Neumann:
Adversarial Imitation Learning with Preferences. ICLR 2023 - [c105]Michael Volpp, Philipp Dahlinger, Philipp Becker, Christian Daniel, Gerhard Neumann:
Accurate Bayesian Meta-Learning by Accurate Task Posterior Inference. ICLR 2023 - [c104]Maximilian Xiling Li, Onur Celik, Philipp Becker, Denis Blessing, Rudolf Lioutikov, Gerhard Neumann:
Curriculum-Based Imitation of Versatile Skills. ICRA 2023: 2951-2957 - [c103]Denis Blessing, Onur Celik, Xiaogang Jia, Moritz Reuss, Maximilian Xiling Li, Rudolf Lioutikov, Gerhard Neumann:
Information Maximizing Curriculum: A Curriculum-Based Approach for Learning Versatile Skills. NeurIPS 2023 - [c102]Niklas Freymuth, Philipp Dahlinger, Tobias Würth, Simon Reisch, Luise Kärger, Gerhard Neumann:
Swarm Reinforcement Learning for Adaptive Mesh Refinement. NeurIPS 2023 - [c101]Florian Seligmann, Philipp Becker, Michael Volpp, Gerhard Neumann:
Beyond Deep Ensembles: A Large-Scale Evaluation of Bayesian Deep Learning under Distribution Shift. NeurIPS 2023 - [c100]Vaisakh Shaj, Saleh Gholam Zadeh, Ozan Demir, Luiz R. Douat, Gerhard Neumann:
Multi Time Scale World Models. NeurIPS 2023 - [i62]Philipp Becker, Sebastian Markgraf, Fabian Otto, Gerhard Neumann:
Reinforcement Learning from Multiple Sensors via Joint Representations. CoRR abs/2302.05342 (2023) - [i61]Paul Maria Scheikl, Balázs Gyenes, Rayan Younis, Christoph Haas, Gerhard Neumann, Martin Wagner, Franziska Mathis-Ullrich:
LapGym - An Open Source Framework for Reinforcement Learning in Robot-Assisted Laparoscopic Surgery. CoRR abs/2302.09606 (2023) - [i60]Jonas Linkerhägner, Niklas Freymuth, Paul Maria Scheikl, Franziska Mathis-Ullrich, Gerhard Neumann:
Grounding Graph Network Simulators using Physical Sensor Observations. CoRR abs/2302.11864 (2023) - [i59]Denis Blessing, Onur Celik, Xiaogang Jia, Moritz Reuss, Maximilian Xiling Li, Rudolf Lioutikov, Gerhard Neumann:
Information Maximizing Curriculum: A Curriculum-Based Approach for Training Mixtures of Experts. CoRR abs/2303.15349 (2023) - [i58]Niklas Freymuth, Philipp Dahlinger, Tobias Würth, Luise Kärger, Gerhard Neumann:
Swarm Reinforcement Learning For Adaptive Mesh Refinement. CoRR abs/2304.00818 (2023) - [i57]Maximilian Xiling Li, Onur Celik, Philipp Becker, Denis Blessing, Rudolf Lioutikov, Gerhard Neumann:
Curriculum-Based Imitation of Versatile Skills. CoRR abs/2304.05171 (2023) - [i56]Florian Seligmann, Philipp Becker, Michael Volpp, Gerhard Neumann:
Beyond Deep Ensembles: A Large-Scale Evaluation of Bayesian Deep Learning under Distribution Shift. CoRR abs/2306.12306 (2023) - [i55]Fabian Otto, Hongyi Zhou, Onur Celik, Ge Li, Rudolf Lioutikov, Gerhard Neumann:
MP3: Movement Primitive-Based (Re-)Planning Policy. CoRR abs/2306.12729 (2023) - [i54]Fabian Duffhauss, Sebastian Koch, Hanna Ziesche, Ngo Anh Vien, Gerhard Neumann:
SyMFM6D: Symmetry-aware Multi-directional Fusion for Multi-View 6D Object Pose Estimation. CoRR abs/2307.00306 (2023) - [i53]Philipp Blättner, Johannes Brand, Gerhard Neumann, Ngo Anh Vien:
DMFC-GraspNet: Differentiable Multi-Fingered Robotic Grasp Generation in Cluttered Scenes. CoRR abs/2308.00456 (2023) - [i52]Ning Gao, Bernard Hohmann, Gerhard Neumann:
Enhancing Interpretable Object Abstraction via Clustering-based Slot Initialization. CoRR abs/2308.11369 (2023) - [i51]Ning Gao, Ngo Anh Vien, Hanna Ziesche, Gerhard Neumann:
SA6D: Self-Adaptive Few-Shot 6D Pose Estimator for Novel and Occluded Objects. CoRR abs/2308.16528 (2023) - [i50]Vaisakh Shaj, Saleh Gholam Zadeh, Ozan Demir, Luiz Ricardo Douat, Gerhard Neumann:
Multi Time Scale World Models. CoRR abs/2310.18534 (2023) - [i49]Philipp Dahlinger, Philipp Becker, Maximilian Hüttenrauch, Gerhard Neumann:
Information-Theoretic Trust Regions for Stochastic Gradient-Based Optimization. CoRR abs/2310.20574 (2023) - [i48]Philipp Dahlinger, Niklas Freymuth, Michael Volpp, Tai Hoang, Gerhard Neumann:
Latent Task-Specific Graph Network Simulators. CoRR abs/2311.05256 (2023) - [i47]Pit Henrich, Balázs Gyenes, Paul Maria Scheikl, Gerhard Neumann, Franziska Mathis-Ullrich:
Registered and Segmented Deformable Object Reconstruction from a Single View Point Cloud. CoRR abs/2311.07357 (2023) - [i46]Paul Maria Scheikl, Nicolas Schreiber, Christoph Haas, Niklas Freymuth, Gerhard Neumann, Rudolf Lioutikov, Franziska Mathis-Ullrich:
Movement Primitive Diffusion: Learning Gentle Robotic Manipulation of Deformable Objects. CoRR abs/2312.10008 (2023) - [i45]Benjamin Alt, Urs Keßner, Aleksandar Taranovic, Darko Katic, Andreas Hermann, Rainer Jäkel, Gerhard Neumann:
Domain-Specific Fine-Tuning of Large Language Models for Interactive Robot Programming. CoRR abs/2312.13905 (2023) - 2022
- [j41]Philipp Becker, Gerhard Neumann:
On Uncertainty in Deep State Space Models for Model-Based Reinforcement Learning. Trans. Mach. Learn. Res. 2022 (2022) - [c99]Fabian Otto, Onur Celik, Hongyi Zhou, Hanna Ziesche, Ngo Anh Vien, Gerhard Neumann:
Deep Black-Box Reinforcement Learning with Movement Primitives. CoRL 2022: 1244-1265 - [c98]Niklas Freymuth, Nicolas Schreiber, Aleksandar Taranovic, Philipp Becker, Gerhard Neumann:
Inferring Versatile Behavior from Demonstrations by Matching Geometric Descriptors. CoRL 2022: 1379-1389 - [c97]Ning Gao, Hanna Ziesche, Ngo Anh Vien, Michael Volpp, Gerhard Neumann:
What Matters For Meta-Learning Vision Regression Tasks? CVPR 2022: 14756-14766 - [c96]Fabian Duffhauss, Ngo Anh Vien, Hanna Ziesche, Gerhard Neumann:
FusionVAE: A Deep Hierarchical Variational Autoencoder for RGB Image Fusion. ECCV (39) 2022: 674-691 - [c95]Vaisakh Shaj, Dieter Büchler, Rohit Sonker, Philipp Becker, Gerhard Neumann:
Hidden Parameter Recurrent State Space Models For Changing Dynamics Scenarios. ICLR 2022 - [c94]Baris Serhan, Harit Pandya, Ayse Küçükyilmaz, Gerhard Neumann:
Push-to-See: Learning Non-Prehensile Manipulation to Enhance Instance Segmentation via Deep Q-Learning. ICRA 2022: 1513-1519 - [c93]Oussama Zenkri, Ngo Anh Vien, Gerhard Neumann:
Hierarchical Policy Learning for Mechanical Search. ICRA 2022: 1954-1960 - [c92]Fabian Duffhauss, Tobias Demmler, Gerhard Neumann:
MV6D: Multi-View 6D Pose Estimation on RGB-D Frames Using a Deep Point-wise Voting Network. IROS 2022: 3568-3575 - [c91]Abdalkarim Mohtasib, Gerhard Neumann, Heriberto Cuayáhuitl:
Robot Policy Learning from Demonstration Using Advantage Weighting and Early Termination. IROS 2022: 7414-7420 - [c90]Moritz Reuss, Niels van Duijkeren, Robert Krug, Philipp Becker, Vaisakh Shaj, Gerhard Neumann:
End-to-End Learning of Hybrid Inverse Dynamics Models for Precise and Compliant Impedance Control. Robotics: Science and Systems 2022 - [i44]Oussama Zenkri, Ngo Anh Vien, Gerhard Neumann:
Hierarchical Policy Learning for Mechanical Search. CoRR abs/2202.13680 (2022) - [i43]Ning Gao, Hanna Ziesche, Ngo Anh Vien, Michael Volpp, Gerhard Neumann:
What Matters For Meta-Learning Vision Regression Tasks? CoRR abs/2203.04905 (2022) - [i42]Hadi Beik-Mohammadi, Søren Hauberg, Georgios Arvanitidis, Gerhard Neumann, Leonel Dario Rozo:
Reactive Motion Generation on Learned Riemannian Manifolds. CoRR abs/2203.07761 (2022) - [i41]Ruijie Chen, Ning Gao, Ngo Anh Vien, Hanna Ziesche, Gerhard Neumann:
Meta-Learning Regrasping Strategies for Physical-Agnostic Objects. CoRR abs/2205.11110 (2022) - [i40]Moritz Reuss, Niels van Duijkeren, Robert Krug, Philipp Becker, Vaisakh Shaj, Gerhard Neumann:
End-to-End Learning of Hybrid Inverse Dynamics Models for Precise and Compliant Impedance Control. CoRR abs/2205.13804 (2022) - [i39]Maximilian Hüttenrauch, Gerhard Neumann:
Regret-Aware Black-Box Optimization with Natural Gradients, Trust-Regions and Entropy Control. CoRR abs/2206.06090 (2022) - [i38]Yumeng Li, Ning Gao, Hanna Ziesche, Gerhard Neumann:
Category-Agnostic 6D Pose Estimation with Conditional Neural Processes. CoRR abs/2206.07162 (2022) - [i37]Vaisakh Shaj, Dieter Buchler, Rohit Sonker, Philipp Becker, Gerhard Neumann:
Hidden Parameter Recurrent State Space Models For Changing Dynamics Scenarios. CoRR abs/2206.14697 (2022) - [i36]Abdalkarim Mohtasib, Gerhard Neumann, Heriberto Cuayáhuitl:
Robot Policy Learning from Demonstration Using Advantage Weighting and Early Termination. CoRR abs/2208.00478 (2022) - [i35]Fabian Duffhauss, Tobias Demmler, Gerhard Neumann:
MV6D: Multi-View 6D Pose Estimation on RGB-D Frames Using a Deep Point-wise Voting Network. CoRR abs/2208.01172 (2022) - [i34]Fabian Duffhauss, Ngo Anh Vien, Hanna Ziesche, Gerhard Neumann:
FusionVAE: A Deep Hierarchical Variational Autoencoder for RGB Image Fusion. CoRR abs/2209.11277 (2022) - [i33]Oleg Arenz, Philipp Dahlinger, Zihan Ye, Michael Volpp, Gerhard Neumann:
A Unified Perspective on Natural Gradient Variational Inference with Gaussian Mixture Models. CoRR abs/2209.11533 (2022) - [i32]Ge Li, Zeqi Jin, Michael Volpp, Fabian Otto, Rudolf Lioutikov, Gerhard Neumann:
ProDMPs: A Unified Perspective on Dynamic and Probabilistic Movement Primitives. CoRR abs/2210.01531 (2022) - [i31]Niklas Freymuth, Nicolas Schreiber, Philipp Becker, Aleksandar Taranovic, Gerhard Neumann:
Inferring Versatile Behavior from Demonstrations by Matching Geometric Descriptors. CoRR abs/2210.08121 (2022) - [i30]Philipp Becker, Gerhard Neumann:
On Uncertainty in Deep State Space Models for Model-Based Reinforcement Learning. CoRR abs/2210.09256 (2022) - [i29]Fabian Otto, Onur Celik, Hongyi Zhou, Hanna Ziesche, Ngo Anh Vien, Gerhard Neumann:
Deep Black-Box Reinforcement Learning with Movement Primitives. CoRR abs/2210.09622 (2022) - 2021
- [j40]R. B. Ashith Shyam, Zhou Hao, Umberto Montanaro, Shilp Dixit, Arunkumar Rathinam, Yang Gao, Gerhard Neumann, Saber Fallah:
Autonomous Robots for Space: Trajectory Learning and Adaptation Using Imitation. Frontiers Robotics AI 8: 638849 (2021) - [j39]Riccardo Polvara, Francesco Del Duchetto, Gerhard Neumann, Marc Hanheide:
Navigate-and-Seek: A Robotics Framework for People Localization in Agricultural Environments. IEEE Robotics Autom. Lett. 6(4): 6577-6584 (2021) - [j38]Juan Parras, Maximilian Hüttenrauch, Santiago Zazo, Gerhard Neumann:
Deep Reinforcement Learning for Attacking Wireless Sensor Networks. Sensors 21(12): 4060 (2021) - [c89]Onur Celik, Dongzhuoran Zhou, Ge Li, Philipp Becker, Gerhard Neumann:
Specializing Versatile Skill Libraries using Local Mixture of Experts. CoRL 2021: 1423-1433 - [c88]Maximilian Hüttenrauch, Gerhard Neumann:
Coordinate ascent MORE with adaptive entropy control for population-based regret minimization. GECCO Companion 2021: 1493-1497 - [c87]Fabian Otto, Philipp Becker, Ngo Anh Vien, Hanna Carolin Maria Ziesche, Gerhard Neumann:
Differentiable Trust Region Layers for Deep Reinforcement Learning. ICLR 2021 - [c86]Michael Volpp, Fabian Flürenbrock, Lukas Großberger, Christian Daniel, Gerhard Neumann:
Bayesian Context Aggregation for Neural Processes. ICLR 2021 - [c85]Paul Maria Scheikl, Balázs Gyenes, Tornike Davitashvili, Rayan Younis, André Schulze, Beat P. Müller-Stich, Gerhard Neumann, Martin Wagner, Franziska Mathis-Ullrich:
Cooperative Assistance in Robotic Surgery through Multi-Agent Reinforcement Learning. IROS 2021: 1859-1864 - [c84]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 - [c83]Kim Tien Ly, Mithun Poozhiyil, Harit Pandya, Gerhard Neumann, Ayse Küçükyilmaz:
Intent-Aware Predictive Haptic Guidance and its Application to Shared Control Teleoperation. RO-MAN 2021: 565-572 - [c82]Hadi Beik-Mohammadi, Søren Hauberg, Georgios Arvanitidis, Gerhard Neumann, Leonel Dario Rozo:
Learning Riemannian Manifolds for Geodesic Motion Skills. Robotics: Science and Systems 2021 - [c81]Abdalkarim Mohtasib, Gerhard Neumann, Heriberto Cuayáhuitl:
A Study on Dense and Sparse (Visual) Rewards in Robot Policy Learning. TAROS 2021: 3-13 - [e1]Aleksandra Faust, David Hsu, Gerhard Neumann:
Conference on Robot Learning, 8-11 November 2021, London, UK. Proceedings of Machine Learning Research 164, PMLR 2021 [contents] - [i28]Fabian Otto, Philipp Becker, Ngo Anh Vien, Hanna Carolin Ziesche, Gerhard Neumann:
Differentiable Trust Region Layers for Deep Reinforcement Learning. CoRR abs/2101.09207 (2021) - [i27]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) - [i26]Hadi Beik-Mohammadi, Søren Hauberg, Georgios Arvanitidis, Gerhard Neumann, Leonel Dario Rozo:
Learning Riemannian Manifolds for Geodesic Motion Skills. CoRR abs/2106.04315 (2021) - [i25]Ngo Anh Vien, Gerhard Neumann:
Differentiable Robust LQR Layers. CoRR abs/2106.05535 (2021) - [i24]Riccardo Polvara, Francesco Del Duchetto, Gerhard Neumann, Marc Hanheide:
Navigate-and-Seek: a Robotics Framework for People Localization in Agricultural Environments. CoRR abs/2107.03850 (2021) - [i23]Abdalkarim Mohtasib, Gerhard Neumann, Heriberto Cuayáhuitl:
A Study on Dense and Sparse (Visual) Rewards in Robot Policy Learning. CoRR abs/2108.03222 (2021) - [i22]Paul Maria Scheikl, Balázs Gyenes, Tornike Davitashvili, Rayan Younis, André Schulze, Beat P. Müller-Stich, Gerhard Neumann, Martin Wagner, Franziska Mathis-Ullrich:
Cooperative Assistance in Robotic Surgery through Multi-Agent Reinforcement Learning. CoRR abs/2110.04857 (2021) - [i21]Niklas Freymuth, Philipp Becker, Gerhard Neumann:
Versatile Inverse Reinforcement Learning via Cumulative Rewards. CoRR abs/2111.07667 (2021) - [i20]Giao Nguyen-Quynh, Philipp Becker, Chen Qiu, Maja Rudolph, Gerhard Neumann:
Switching Recurrent Kalman Networks. CoRR abs/2111.08291 (2021) - [i19]Jairo Inga, Miriam Ruess, Jan Heinrich Robens, Thomas Nelius, Sean Kille, Philipp Dahlinger, Roland Thomaschke, Gerhard Neumann, Sven Matthiesen, Sören Hohmann, Andrea Kiesel:
Human-machine Symbiosis: A Multivariate Perspective for Physically Coupled Human-machine Systems. CoRR abs/2111.14681 (2021) - [i18]Onur Celik, Dongzhuoran Zhou, Ge Li, Philipp Becker, Gerhard Neumann:
Specializing Versatile Skill Libraries using Local Mixture of Experts. CoRR abs/2112.04216 (2021) - 2020
- [j37]Oleg Arenz, Mingjun Zhong, Gerhard Neumann:
Trust-Region Variational Inference with Gaussian Mixture Models. J. Mach. Learn. Res. 21: 163:1-163:60 (2020) - [j36]Riccardo Polvara, Manuel Fernández-Carmona, Gerhard Neumann, Marc Hanheide:
Next-Best-Sense: A Multi-Criteria Robotic Exploration Strategy for RFID Tags Discovery. IEEE Robotics Autom. Lett. 5(3): 4477-4484 (2020) - [j35]Joni Pajarinen, Oleg Arenz, Jan Peters, Gerhard Neumann:
Probabilistic Approach to Physical Object Disentangling. IEEE Robotics Autom. Lett. 5(4): 5510-5517 (2020) - [j34]Riccardo Polvara, Massimiliano Patacchiola, Marc Hanheide, Gerhard Neumann:
Sim-to-Real Quadrotor Landing via Sequential Deep Q-Networks and Domain Randomization. Robotics 9(1): 8 (2020) - [j33]Jayant Singh, Aravinda Ramakrishnan Srinivasan, Gerhard Neumann, Ayse Küçükyilmaz:
Haptic-Guided Teleoperation of a 7-DoF Collaborative Robot Arm With an Identical Twin Master. IEEE Trans. Haptics 13(1): 246-252 (2020) - [j32]Firas Abi-Farraj, Claudio Pacchierotti, Oleg Arenz, Gerhard Neumann, Paolo Robuffo Giordano:
A Haptic Shared-Control Architecture for Guided Multi-Target Robotic Grasping. IEEE Trans. Haptics 13(2): 270-285 (2020) - [j31]Sebastián Gómez-González, Gerhard Neumann, Bernhard Schölkopf, Jan Peters:
Adaptation and Robust Learning of Probabilistic Movement Primitives. IEEE Trans. Robotics 36(2): 366-379 (2020) - [c80]Soran Parsa, Disha Kamale, Sariah Mghames, Kiyanoush Nazari, Tommaso Pardi, Aravinda Ramakrishnan Srinivasan, Gerhard Neumann, Marc Hanheide, Amir Ghalamzan E:
Haptic-guided shared control grasping: collision-free manipulation. CASE 2020: 1552-1557 - [c79]Vaisakh Shaj, Philipp Becker, Dieter Büchler, Harit Pandya, Niels van Duijkeren, C. James Taylor, Marc Hanheide, Gerhard Neumann:
Action-Conditional Recurrent Kalman Networks For Forward and Inverse Dynamics Learning. CoRL 2020: 765-781 - [c78]Philipp Becker, Oleg Arenz, Gerhard Neumann:
Expected Information Maximization: Using the I-Projection for Mixture Density Estimation. ICLR 2020 - [c77]Mohamed Sorour, Khaled Elgeneidy, Marc Hanheide, M. Abdalmjed, A. Srinivasan, Gerhard Neumann:
Enhancing Grasp Pose Computation in Gripper Workspace Spheres. ICRA 2020: 1539-1545 - [i17]Philipp Becker, Oleg Arenz, Gerhard Neumann:
Expected Information Maximization: Using the I-Projection for Mixture Density Estimation. CoRR abs/2001.08682 (2020) - [i16]Joni Pajarinen, Oleg Arenz, Jan Peters, Gerhard Neumann:
Probabilistic approach to physical object disentangling. CoRR abs/2002.11495 (2020) - [i15]Oleg Arenz, Gerhard Neumann:
Non-Adversarial Imitation Learning and its Connections to Adversarial Methods. CoRR abs/2008.03525 (2020) - [i14]R. B. Ashith Shyam, Zhou Hao, Umberto Montanaro, Gerhard Neumann:
Imitation Learning for Autonomous Trajectory Learning of Robot Arms in Space. CoRR abs/2008.04007 (2020) - [i13]Vaisakh Shaj, Philipp Becker, Dieter Buchler, Harit Pandya, Niels van Duijkeren, C. James Taylor, Marc Hanheide, Gerhard Neumann:
Action-Conditional Recurrent Kalman Networks For Forward and Inverse Dynamics Learning. CoRR abs/2010.10201 (2020)
2010 – 2019
- 2019
- [j30]Abbas Abdolmaleki, David Simões, Nuno Lau, Luís Paulo Reis, Gerhard Neumann:
Contextual Direct Policy Search - With Regularized Covariance Matrix Estimation. J. Intell. Robotic Syst. 96(2): 141-157 (2019) - [j29]Maximilian Hüttenrauch, Adrian Sosic, Gerhard Neumann:
Deep Reinforcement Learning for Swarm Systems. J. Mach. Learn. Res. 20: 54:1-54:31 (2019) - [j28]Joni Pajarinen, Hong Linh Thai, Riad Akrour, Jan Peters, Gerhard Neumann:
Compatible natural gradient policy search. Mach. Learn. 108(8-9): 1443-1466 (2019) - [j27]Gregor H. W. Gebhardt, Andras Gabor Kupcsik, Gerhard Neumann:
The kernel Kalman rule - Efficient nonparametric inference by recursive least-squares and subspace projections. Mach. Learn. 108(12): 2113-2157 (2019) - [j26]Florian Brandherm, Jan Peters, Gerhard Neumann, Riad Akrour:
Learning Replanning Policies With Direct Policy Search. IEEE Robotics Autom. Lett. 4(2): 2196-2203 (2019) - [j25]Cheng Zhao, Li Sun, Zhi Yan, Gerhard Neumann, Tom Duckett, Rustam Stolkin:
Learning Kalman Network: A deep monocular visual odometry for on-road driving. Robotics Auton. Syst. 121 (2019) - [c76]Riad Akrour, Joni Pajarinen, Jan Peters, Gerhard Neumann:
Projections for Approximate Policy Iteration Algorithms. ICML 2019: 181-190 - [c75]Philipp Becker, Harit Pandya, Gregor H. W. Gebhardt, Cheng Zhao, C. James Taylor, Gerhard Neumann:
Recurrent Kalman Networks: Factorized Inference in High-Dimensional Deep Feature Spaces. ICML 2019: 544-552 - [c74]Mohamed Sorour, Khaled Elgeneidy, Aravinda Srinivasan, Marc Hanheide, Gerhard Neumann:
Grasping Unknown Objects Based on Gripper Workspace Spheres. IROS 2019: 1541-1547 - [c73]R. B. Ashith Shyam, Peter Lightbody, Gautham Das, Pengcheng Liu, Sebastián Gómez-González, Gerhard Neumann:
Improving Local Trajectory Optimisation using Probabilistic Movement Primitives. IROS 2019: 2666-2671 - [c72]Khaled Elgeneidy, Peter Lightbody, Simon Pearson, Gerhard Neumann:
Characterising 3D-printed Soft Fin Ray Robotic Fingers with Layer Jamming Capability for Delicate Grasping. RoboSoft 2019: 143-148 - [i12]Joni Pajarinen, Hong Linh Thai, Riad Akrour, Jan Peters, Gerhard Neumann:
Compatible Natural Gradient Policy Search. CoRR abs/1902.02823 (2019) - [i11]Philipp Becker, Harit Pandya, Gregor H. W. Gebhardt, Cheng Zhao, C. James Taylor, Gerhard Neumann:
Recurrent Kalman Networks: Factorized Inference in High-Dimensional Deep Feature Spaces. CoRR abs/1905.07357 (2019) - [i10]Oleg Arenz, Mingjun Zhong, Gerhard Neumann:
Trust-Region Variational Inference with Gaussian Mixture Models. CoRR abs/1907.04710 (2019) - 2018
- [j24]Alexandros Paraschos, Elmar Rueckert, Jan Peters, Gerhard Neumann:
Probabilistic movement primitives under unknown system dynamics. Adv. Robotics 32(6): 297-310 (2018) - [j23]Takayuki Osa, Jan Peters, Gerhard Neumann:
Hierarchical reinforcement learning of multiple grasping strategies with human instructions. Adv. Robotics 32(18): 955-968 (2018) - [j22]Alexandros Paraschos, Christian Daniel, Jan Peters, Gerhard Neumann:
Using probabilistic movement primitives in robotics. Auton. Robots 42(3): 529-551 (2018) - [j21]Khaled Elgeneidy, Gerhard Neumann, Michael R. Jackson, Niels Lohse:
Directly Printable Flexible Strain Sensors for Bending and Contact Feedback of Soft Actuators. Frontiers Robotics AI 5: 2 (2018) - [j20]Takayuki Osa, Joni Pajarinen, Gerhard Neumann, J. Andrew Bagnell, Pieter Abbeel, Jan Peters:
An Algorithmic Perspective on Imitation Learning. Found. Trends Robotics 7(1-2): 1-179 (2018) - [j19]Riad Akrour, Abbas Abdolmaleki, Hany Abdulsamad, Jan Peters, Gerhard Neumann:
Model-Free Trajectory-based Policy Optimization with Monotonic Improvement. J. Mach. Learn. Res. 19: 14:1-14:25 (2018) - [c71]Maximilian Hüttenrauch, Adrian Sosic, Gerhard Neumann:
Local Communication Protocols for Learning Complex Swarm Behaviors with Deep Reinforcement Learning. ANTS Conference 2018: 71-83 - [c70]Oleg Arenz, Mingjun Zhong, Gerhard Neumann:
Efficient Gradient-Free Variational Inference using Policy Search. ICML 2018: 234-243 - [c69]Robert Pinsler, Riad Akrour, Takayuki Osa, Jan Peters, Gerhard Neumann:
Sample and Feedback Efficient Hierarchical Reinforcement Learning from Human Preferences. ICRA 2018: 596-601 - [c68]Dorothea Koert, Guilherme Maeda, Gerhard Neumann, Jan Peters:
Learning Coupled Forward-Inverse Models with Combined Prediction Errors. ICRA 2018: 2433-2439 - [c67]Gregor H. W. Gebhardt, Kevin Daun, Marius Schnaubelt, Gerhard Neumann:
Learning Robust Policies for Object Manipulation with Robot Swarms. ICRA 2018: 7688-7695 - [c66]Khaled Elgeneidy, Gerhard Neumann, Simon Pearson, Michael R. Jackson, Niels Lohse:
Contact Detection and Size Estimation Using a Modular Soft Gripper with Embedded Flex Sensors. IROS 2018: 498-503 - [c65]Riad Akrour, Filipe Veiga, Jan Peters, Gerhard Neumann:
Regularizing Reinforcement Learning with State Abstraction. IROS 2018: 534-539 - [c64]Pengcheng Liu, Gerhard Neumann, Qinbing Fu, Simon Pearson, Hongnian Yu:
Energy-Efficient Design and Control of a Vibro-Driven Robot. IROS 2018: 1464-1469 - [i9]Maximilian Hüttenrauch, Adrian Sosic, Gerhard Neumann:
Deep Reinforcement Learning for Swarm Systems. CoRR abs/1807.06613 (2018) - [i8]Patrick Jahnke, Emmanuel Stapf, Jonas Mieseler, Gerhard Neumann, Patrick Eugster:
Towards Fine Grained Network Flow Prediction. CoRR abs/1808.06453 (2018) - [i7]Sebastián Gómez-González, Gerhard Neumann, Bernhard Schölkopf, Jan Peters:
Adaptation and Robust Learning of Probabilistic Movement Primitives. CoRR abs/1808.10648 (2018) - [i6]Takayuki Osa, Joni Pajarinen, Gerhard Neumann, J. Andrew Bagnell, Pieter Abbeel, Jan Peters:
An Algorithmic Perspective on Imitation Learning. CoRR abs/1811.06711 (2018) - 2017
- [j18]Andras Gabor Kupcsik, Marc Peter Deisenroth, Jan Peters, Ai Poh Loh, Prahlad Vadakkepat, Gerhard Neumann:
Model-based contextual policy search for data-efficient generalization of robot skills. Artif. Intell. 247: 415-439 (2017) - [j17]Guilherme Maeda, Gerhard Neumann, Marco Ewerton, Rudolf Lioutikov, Oliver Kroemer, Jan Peters:
Probabilistic movement primitives for coordination of multiple human-robot collaborative tasks. Auton. Robots 41(3): 593-612 (2017) - [j16]Rudolf Lioutikov, Gerhard Neumann, Guilherme Maeda, Jan Peters:
Learning movement primitive libraries through probabilistic segmentation. Int. J. Robotics Res. 36(8): 879-894 (2017) - [j15]Guilherme Maeda, Marco Ewerton, Gerhard Neumann, Rudolf Lioutikov, Jan Peters:
Phase estimation for fast action recognition and trajectory generation in human-robot collaboration. Int. J. Robotics Res. 36(13-14): 1579-1594 (2017) - [j14]Herke van Hoof, Gerhard Neumann, Jan Peters:
Non-parametric Policy Search with Limited Information Loss. J. Mach. Learn. Res. 18: 73:1-73:46 (2017) - [j13]Christian Wirth, Riad Akrour, Gerhard Neumann, Johannes Fürnkranz:
A Survey of Preference-Based Reinforcement Learning Methods. J. Mach. Learn. Res. 18: 136:1-136:46 (2017) - [j12]Takayuki Osa, Amir Masoud Ghalamzan Esfahani, Rustam Stolkin, Rudolf Lioutikov, Jan Peters, Gerhard Neumann:
Guiding Trajectory Optimization by Demonstrated Distributions. IEEE Robotics Autom. Lett. 2(2): 819-826 (2017) - [j11]Alexandros Paraschos, Rudolf Lioutikov, Jan Peters, Gerhard Neumann:
Probabilistic Prioritization of Movement Primitives. IEEE Robotics Autom. Lett. 2(4): 2294-2301 (2017) - [c63]Abbas Abdolmaleki, David Simões, Nuno Lau, Luís Paulo Reis, Bob Price, Gerhard Neumann:
Stochastic Search In Changing Situations. AAAI Workshops 2017 - [c62]Voot Tangkaratt, Herke van Hoof, Simone Parisi, Gerhard Neumann, Jan Peters, Masashi Sugiyama:
Policy Search with High-Dimensional Context Variables. AAAI 2017: 2632-2638 - [c61]Gregor H. W. Gebhardt, Andras Gabor Kupcsik, Gerhard Neumann:
The Kernel Kalman Rule - Efficient Nonparametric Inference with Recursive Least Squares. AAAI 2017: 3754-3760 - [c60]Hany Abdulsamad, Oleg Arenz, Jan Peters, Gerhard Neumann:
State-Regularized Policy Search for Linearized Dynamical Systems. ICAPS 2017: 419-424 - [c59]Gregor H. W. Gebhardt, Kevin Daun, Marius Schnaubelt, Alexander Hendrich, Daniel Kauth, Gerhard Neumann:
Learning to Assemble Objects with a Robot Swarm. AAMAS 2017: 1547-1549 - [c58]Abbas Abdolmaleki, Bob Price, Nuno Lau, Luís Paulo Reis, Gerhard Neumann:
Deriving and improving CMA-ES with information geometric trust regions. GECCO 2017: 657-664 - [c57]Riad Akrour, Dmitry Sorokin, Jan Peters, Gerhard Neumann:
Local Bayesian Optimization of Motor Skills. ICML 2017: 41-50 - [c56]Firas Abi-Farraj, Takayuki Osa, Nicolo Pedemonte, Jan Peters, Gerhard Neumann, Paolo Robuffo Giordano:
A learning-based shared control architecture for interactive task execution. ICRA 2017: 329-335 - [c55]Alexander Gabriel, Riad Akrour, Jan Peters, Gerhard Neumann:
Empowered skills. ICRA 2017: 6435-6441 - [c54]Felix End, Riad Akrour, Jan Peters, Gerhard Neumann:
Layered direct policy search for learning hierarchical skills. ICRA 2017: 6442-6448 - [c53]Abbas Abdolmaleki, Bob Price, Nuno Lau, Luís Paulo Reis, Gerhard Neumann:
Contextual Covariance Matrix Adaptation Evolutionary Strategies. IJCAI 2017: 1378-1385 - [c52]Joni Pajarinen, Ville Kyrki, Michael C. Koval, Siddhartha S. Srinivasa, Jan Peters, Gerhard Neumann:
Hybrid control trajectory optimization under uncertainty. IROS 2017: 5694-5701 - [i5]Joni Pajarinen, Ville Kyrki, Michael C. Koval, Siddhartha S. Srinivasa, Jan Peters, Gerhard Neumann:
Hybrid control trajectory optimization under uncertainty. CoRR abs/1702.04396 (2017) - [i4]Maximilian Hüttenrauch, Adrian Sosic, Gerhard Neumann:
Guided Deep Reinforcement Learning for Swarm Systems. CoRR abs/1709.06011 (2017) - [i3]Maximilian Hüttenrauch, Adrian Sosic, Gerhard Neumann:
Learning Complex Swarm Behaviors by Exploiting Local Communication Protocols with Deep Reinforcement Learning. CoRR abs/1709.07224 (2017) - 2016
- [j10]Abbas Abdolmaleki, Nuno Lau, Luís Paulo Reis, Jan Peters, Gerhard Neumann:
Contextual Policy Search for Linear and Nonlinear Generalization of a Humanoid Walking Controller. J. Intell. Robotic Syst. 83(3-4): 393-408 (2016) - [j9]Christian Daniel, Gerhard Neumann, Oliver Kroemer, Jan Peters:
Hierarchical Relative Entropy Policy Search. J. Mach. Learn. Res. 17: 93:1-93:50 (2016) - [j8]Christian Daniel, Herke van Hoof, Jan Peters, Gerhard Neumann:
Probabilistic inference for determining options in reinforcement learning. Mach. Learn. 104(2-3): 337-357 (2016) - [c51]Christian Wirth, Johannes Fürnkranz, Gerhard Neumann:
Model-Free Preference-Based Reinforcement Learning. AAAI 2016: 2222-2228 - [c50]Abbas Abdolmaleki, Nuno Lau, Luís Paulo Reis, Gerhard Neumann:
Contextual Stochastic Search. GECCO (Companion) 2016: 29-30 - [c49]Abbas Abdolmaleki, Rudolf Lioutikov, Nuno Lau, Luís Paulo Reis, Jan Peters, Gerhard Neumann:
Model-Based Relative Entropy Stochastic Search. GECCO (Companion) 2016: 153-154 - [c48]Sebastián Gómez-González, Gerhard Neumann, Bernhard Schölkopf, Jan Peters:
Using probabilistic movement primitives for striking movements. Humanoids 2016: 502-508 - [c47]Dorothea Koert, Guilherme Maeda, Rudolf Lioutikov, Gerhard Neumann, Jan Peters:
Demonstration based trajectory optimization for generalizable robot motions. Humanoids 2016: 515-522 - [c46]Abbas Abdolmaleki, David Simões, Nuno Lau, Luís Paulo Reis, Gerhard Neumann:
Contextual Relative Entropy Policy Search with Covariance Matrix Adaptation. ICARSC 2016: 94-99 - [c45]Riad Akrour, Gerhard Neumann, Hany Abdulsamad, Abbas Abdolmaleki:
Model-Free Trajectory Optimization for Reinforcement Learning. ICML 2016: 2961-2970 - [c44]Marco Ewerton, Guilherme Maeda, Gerhard Neumann, Viktor Kisner, Gerrit Kollegger, Josef Wiemeyer, Jan Peters:
Movement primitives with multiple phase parameters. ICRA 2016: 201-206 - [c43]Valerio Modugno, Gerhard Neumann, Elmar Rueckert, Giuseppe Oriolo, Jan Peters, Serena Ivaldi:
Learning soft task priorities for control of redundant robots. ICRA 2016: 221-226 - [c42]Abbas Abdolmaleki, Nuno Lau, Luís Paulo Reis, Gerhard Neumann:
Non-parametric contextual stochastic search. IROS 2016: 2643-2648 - [c41]Oleg Arenz, Hany Abdulsamad, Gerhard Neumann:
Optimal control and inverse optimal control by distribution matching. IROS 2016: 4046-4053 - [c40]Takayuki Osa, Jan Peters, Gerhard Neumann:
Experiments with Hierarchical Reinforcement Learning of Multiple Grasping Policies. ISER 2016: 160-172 - [c39]Boris Belousov, Gerhard Neumann, Constantin A. Rothkopf, Jan Peters:
Catching heuristics are optimal control policies. NIPS 2016: 1426-1434 - [c38]Abbas Abdolmaleki, David Simões, Nuno Lau, Luís Paulo Reis, Gerhard Neumann:
Learning a Humanoid Kick with Controlled Distance. RoboCup 2016: 45-57 - [i2]Riad Akrour, Abbas Abdolmaleki, Hany Abdulsamad, Gerhard Neumann:
Model-free Trajectory Optimization for Reinforcement Learning. CoRR abs/1606.09197 (2016) - [i1]Voot Tangkaratt, Herke van Hoof, Simone Parisi, Gerhard Neumann, Jan Peters, Masashi Sugiyama:
Policy Search with High-Dimensional Context Variables. CoRR abs/1611.03231 (2016) - 2015
- [c37]Christoph Dann, Gerhard Neumann, Jan Peters:
Policy Evaluation with Temporal Differences: A Survey and Comparison (Extended Abstract). ICAPS 2015: 359-360 - [c36]Herke van Hoof, Jan Peters, Gerhard Neumann:
Learning of Non-Parametric Control Policies with High-Dimensional State Features. AISTATS 2015 - [c35]Okan Koc, Guilherme Maeda, Gerhard Neumann, Jan Peters:
Optimizing robot striking movement primitives with Iterative Learning Control. Humanoids 2015: 80-87 - [c34]Herke van Hoof, Tucker Hermans, Gerhard Neumann, Jan Peters:
Learning robot in-hand manipulation with tactile features. Humanoids 2015: 121-127 - [c33]Abbas Abdolmaleki, Nuno Lau, Luís Paulo Reis, Gerhard Neumann:
Regularized covariance estimation for weighted maximum likelihood policy search methods. Humanoids 2015: 154-159 - [c32]Rudolf Lioutikov, Gerhard Neumann, Guilherme Maeda, Jan Peters:
Probabilistic segmentation applied to an assembly task. Humanoids 2015: 533-540 - [c31]Abbas Abdolmaleki, Nuno Lau, Luís Paulo Reis, Jan Peters, Gerhard Neumann:
Contextual Policy Search for Generalizing a Parameterized Biped Walking Controller. ICARSC 2015: 17-22 - [c30]Oliver Kroemer, Christian Daniel, Gerhard Neumann, Herke van Hoof, Jan Peters:
Towards learning hierarchical skills for multi-phase manipulation tasks. ICRA 2015: 1503-1510 - [c29]Elmar Rueckert, Jan Mundo, Alexandros Paraschos, Jan Peters, Gerhard Neumann:
Extracting low-dimensional control variables for movement primitives. ICRA 2015: 1511-1518 - [c28]Marco Ewerton, Gerhard Neumann, Rudolf Lioutikov, Heni Ben Amor, Jan Peters, Guilherme Maeda:
Learning multiple collaborative tasks with a mixture of Interaction Primitives. ICRA 2015: 1535-1542 - [c27]Marco Ewerton, Guilherme Maeda, Jan Peters, Gerhard Neumann:
Learning motor skills from partially observed movements executed at different speeds. IROS 2015: 456-463 - [c26]Alexandros Paraschos, Elmar Rueckert, Jan Peters, Gerhard Neumann:
Model-free Probabilistic Movement Primitives for physical interaction. IROS 2015: 2860-2866 - [c25]Guilherme Maeda, Gerhard Neumann, Marco Ewerton, Rudolf Lioutikov, Jan Peters:
A Probabilistic Framework for Semi-autonomous Robots Based on Interaction Primitives with Phase Estimation. ISRR (2) 2015: 253-268 - [c24]Abbas Abdolmaleki, Rudolf Lioutikov, Jan Peters, Nuno Lau, Luís Paulo Reis, Gerhard Neumann:
Model-Based Relative Entropy Stochastic Search. NIPS 2015: 3537-3545 - 2014
- [j7]Gerhard Neumann, Christian Daniel, Alexandros Paraschos, Andras Gabor Kupcsik, Jan Peters:
Learning modular policies for robotics. Frontiers Comput. Neurosci. 8: 62 (2014) - [j6]Rudolf Lioutikov, Alexandros Paraschos, Jan Peters, Gerhard Neumann:
Generalizing Movements with Information-Theoretic Stochastic Optimal Control. J. Aerosp. Inf. Syst. 11(9): 579-595 (2014) - [j5]Christoph Dann, Gerhard Neumann, Jan Peters:
Policy evaluation with temporal differences: a survey and comparison. J. Mach. Learn. Res. 15(1): 809-883 (2014) - [c23]Elmar Rueckert, Max Mindt, Jan Peters, Gerhard Neumann:
Robust policy updates for stochastic optimal control. Humanoids 2014: 388-393 - [c22]Guilherme Maeda, Marco Ewerton, Rudolf Lioutikov, Heni Ben Amor, Jan Peters, Gerhard Neumann:
Learning interaction for collaborative tasks with probabilistic movement primitives. Humanoids 2014: 527-534 - [c21]Adria Colome, Gerhard Neumann, Jan Peters, Carme Torras:
Dimensionality reduction for probabilistic movement primitives. Humanoids 2014: 794-800 - [c20]Abbas Abdolmaleki, Nima Shafii, Luís Paulo Reis, Nuno Lau, Jan Peters, Gerhard Neumann:
Omnidirectional Walking with a Compliant Inverted Pendulum Model. IBERAMIA 2014: 481-493 - [c19]Heni Ben Amor, Gerhard Neumann, Sanket Kamthe, Oliver Kroemer, Jan Peters:
Interaction primitives for human-robot cooperation tasks. ICRA 2014: 2831-2837 - [c18]Rudolf Lioutikov, Alexandros Paraschos, Jan Peters, Gerhard Neumann:
Sample-based informationl-theoretic stochastic optimal control. ICRA 2014: 3896-3902 - [c17]Oliver Kroemer, Herke van Hoof, Gerhard Neumann, Jan Peters:
Learning to predict phases of manipulation tasks as hidden states. ICRA 2014: 4009-4014 - [c16]Kevin Sebastian Luck, Gerhard Neumann, Erik Berger, Jan Peters, Heni Ben Amor:
Latent space policy search for robotics. IROS 2014: 1434-1440 - [c15]Vicenç Gómez, Hilbert J. Kappen, Jan Peters, Gerhard Neumann:
Policy Search for Path Integral Control. ECML/PKDD (1) 2014: 482-497 - 2013
- [j4]Elmar A. Rückert, Gerhard Neumann:
Stochastic Optimal Control Methods for Investigating the Power of Morphological Computation. Artif. Life 19(1): 115-131 (2013) - [j3]Marc Peter Deisenroth, Gerhard Neumann, Jan Peters:
A Survey on Policy Search for Robotics. Found. Trends Robotics 2(1-2): 1-142 (2013) - [c14]Andras Gabor Kupcsik, Marc Peter Deisenroth, Jan Peters, Gerhard Neumann:
Data-Efficient Generalization of Robot Skills with Contextual Policy Search. AAAI 2013: 1401-1407 - [c13]Alexandros Paraschos, Gerhard Neumann, Jan Peters:
A probabilistic approach to robot trajectory generation. Humanoids 2013: 477-483 - [c12]Christian Daniel, Gerhard Neumann, Oliver Kroemer, Jan Peters:
Learning sequential motor tasks. ICRA 2013: 2626-2632 - [c11]Christian Daniel, Gerhard Neumann, Jan Peters:
Autonomous reinforcement learning with hierarchical REPS. IJCNN 2013: 1-8 - [c10]Alexandros Paraschos, Christian Daniel, Jan Peters, Gerhard Neumann:
Probabilistic Movement Primitives. NIPS 2013: 2616-2624 - [c9]Jan Peters, Jens Kober, Katharina Mülling, Oliver Krömer, Gerhard Neumann:
Towards Robot Skill Learning: From Simple Skills to Table Tennis. ECML/PKDD (3) 2013: 627-631 - 2012
- [j2]Elmar A. Rückert, Gerhard Neumann, Marc Toussaint, Wolfgang Maass:
Learned graphical models for probabilistic planning provide a new class of movement primitives. Frontiers Comput. Neurosci. 6: 97 (2012) - [c8]Heni Ben Amor, Oliver Kroemer, Ulrich Hillenbrand, Gerhard Neumann, Jan Peters:
Generalization of human grasping for multi-fingered robot hands. IROS 2012: 2043-2050 - [c7]Christian Daniel, Gerhard Neumann, Jan Peters:
Learning concurrent motor skills in versatile solution spaces. IROS 2012: 3591-3597 - [c6]Christian Daniel, Gerhard Neumann, Jan Peters:
Hierarchical Relative Entropy Policy Search. AISTATS 2012: 273-281 - 2011
- [j1]Helmut Hauser, Gerhard Neumann, Auke Jan Ijspeert, Wolfgang Maass:
Biologically inspired kinematic synergies enable linear balance control of a humanoid robot. Biol. Cybern. 104(4-5): 235-249 (2011) - [c5]Gerhard Neumann:
Variational Inference for Policy Search in changing situations. ICML 2011: 817-824
2000 – 2009
- 2009
- [c4]Gerhard Neumann, Wolfgang Maass, Jan Peters:
Learning complex motions by sequencing simpler motion templates. ICML 2009: 753-760 - 2008
- [c3]Gerhard Neumann, Jan Peters:
Fitted Q-iteration by Advantage Weighted Regression. NIPS 2008: 1177-1184 - 2007
- [c2]Gerhard Neumann, Michael Pfeiffer, Wolfgang Maass:
Efficient Continuous-Time Reinforcement Learning with Adaptive State Graphs. ECML 2007: 250-261 - [c1]Helmut Hauser, Gerhard Neumann, Auke Jan Ijspeert, Wolfgang Maass:
Biologically inspired kinematic synergies provide a new paradigm for balance control of humanoid robots. Humanoids 2007: 73-80
Coauthor Index
Jan Peters 0001
aka: Jan R. Peters
aka: Jan R. Peters
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