← Authors

Gerhard Neumann

59 papers · 2008–2025 · 11 conferences · across top CS/AI conferences

Achievements

🧭 Keyword Pioneer πŸƒ Academic Marathon (17) 🌍 Conference Polyglot (11) 🐝 Cross-Pollinator (9) πŸŒ‰ Interdisciplinary Bridge 🐣 Hot Topic Early Bird 🌈 Renaissance Researcher (7) πŸ—ΊοΈ Taxonomy Completionist (12) 🀝 Dynamic Duo (13) πŸ‘‘ Triple Crown 🧬 Topic Evolution πŸ‘₯ Mega-Team (22) πŸ”¬ Deep Specialist (14) πŸ† Keyword Champion πŸ“ˆ Trend Setter ⚑ Prolific Year (8) ❓ The Questioner πŸ’Ž Century Club (59) πŸ”₯ Unstoppable (14) πŸ—ƒοΈ Keyword Collector (168)

Conferences

ICLR (16) NIPS (10) JMLR (9) CORL (8) ICML (8) AISTATS (2) RSS (2) CVPR (1) ECCV (1) IJCAI (1) WACV (1)

Top co-authors

Philipp Becker (13) Jan Peters (10) Denis Blessing (9) Rudolf Lioutikov (9) Onur Celik (7) Xiaogang Jia (7) Ge Li (7) Hongyi Zhou (7) Vien Anh Ngo (5) Christian Daniel (5)

Keywords

policy search (5) variational inference (4) reinforcement learning (4) black-box optimization (3) relative entropy (3) mixture of expert (3) movement primitive (3) stochastic search (3) robot learning (3) sample efficiency (3) few-shot learning (2) inverse dynamics (2) maximum entropy (2) object segmentation (2) policy optimization (2) deep reinforcement learning (2) continuous control (2) probabilistic modeling (2) imitation learning (2) policy gradient (2)

Papers

DIME: Diffusion-Based Maximum Entropy Reinforcement Learning ICML 2025
Geometry-aware RL for Manipulation of Varying Shapes and Deformable Objects ICLR 2025
IRIS: An Immersive Robot Interaction System CORL 2025
Efficient Off-Policy Learning for High-Dimensional Action Spaces ICLR 2025
Sequential Controlled Langevin Diffusions ICLR 2025
TOP-ERL: Transformer-based Off-Policy Episodic Reinforcement Learning ICLR 2025
End-to-end Learning of Gaussian Mixture Priors for Diffusion Sampler ICLR 2025
Underdamped Diffusion Bridges with Applications to Sampling ICLR 2025
Acquiring Diverse Skills using Curriculum Reinforcement Learning with Mixture of Experts ICML 2024
A Retrospective on the Robot Air Hockey Challenge: Benchmarking Robust, Reliable, and Safe Learning Techniques for Real-world Robotics NIPS 2024
Variational Distillation of Diffusion Policies into Mixture of Experts NIPS 2024
MaIL: Improving Imitation Learning with Selective State Space Models CORL 2024
PointPatchRL - Masked Reconstruction Improves Reinforcement Learning on Point Clouds CORL 2024
Towards Diverse Behaviors: A Benchmark for Imitation Learning with Human Demonstrations ICLR 2024
Open the Black Box: Step-based Policy Updates for Temporally-Correlated Episodic Reinforcement Learning ICLR 2024
Neural Contractive Dynamical Systems ICLR 2024
Beyond ELBOs: A Large-Scale Evaluation of Variational Methods for Sampling ICML 2024
Robust Black-Box Optimization for Stochastic Search and Episodic Reinforcement Learning JMLR 2024
Registered and Segmented Deformable Object Reconstruction From a Single View Point Cloud WACV 2024
Accurate Bayesian Meta-Learning by Accurate Task Posterior Inference ICLR 2023
Swarm Reinforcement Learning for Adaptive Mesh Refinement NIPS 2023
LapGym - An Open Source Framework for Reinforcement Learning in Robot-Assisted Laparoscopic Surgery JMLR 2023
Multi Time Scale World Models NIPS 2023
Beyond Deep Ensembles: A Large-Scale Evaluation of Bayesian Deep Learning under Distribution Shift NIPS 2023
Information Maximizing Curriculum: A Curriculum-Based Approach for Learning Versatile Skills NIPS 2023
SA6D: Self-Adaptive Few-Shot 6D Pose Estimator for Novel and Occluded Objects CORL 2023
Adversarial Imitation Learning with Preferences ICLR 2023
Grounding Graph Network Simulators using Physical Sensor Observations ICLR 2023
Inferring Versatile Behavior from Demonstrations by Matching Geometric Descriptors CORL 2022
FusionVAE: A Deep Hierarchical Variational Autoencoder for RGB Image Fusion ECCV 2022
Hidden Parameter Recurrent State Space Models For Changing Dynamics Scenarios ICLR 2022
End-to-End Learning of Hybrid Inverse Dynamics Models for Precise and Compliant Impedance Control RSS 2022
What Matters for Meta-Learning Vision Regression Tasks? CVPR 2022
Deep Black-Box Reinforcement Learning with Movement Primitives CORL 2022
Bayesian Context Aggregation for Neural Processes ICLR 2021
Specializing Versatile Skill Libraries using Local Mixture of Experts CORL 2021
Learning Riemannian Manifolds for Geodesic Motion Skills RSS 2021
Differentiable Trust Region Layers for Deep Reinforcement Learning ICLR 2021
Action-Conditional Recurrent Kalman Networks For Forward and Inverse Dynamics Learning CORL 2020
Expected Information Maximization: Using the I-Projection for Mixture Density Estimation ICLR 2020
Trust-Region Variational Inference with Gaussian Mixture Models JMLR 2020
Deep Reinforcement Learning for Swarm Systems JMLR 2019
Projections for Approximate Policy Iteration Algorithms ICML 2019
Recurrent Kalman Networks: Factorized Inference in High-Dimensional Deep Feature Spaces ICML 2019
Model-Free Trajectory-based Policy Optimization with Monotonic Improvement JMLR 2018
Efficient Gradient-Free Variational Inference using Policy Search ICML 2018
A Survey of Preference-Based Reinforcement Learning Methods JMLR 2017
Local Bayesian Optimization of Motor Skills ICML 2017
Contextual Covariance Matrix Adaptation Evolutionary Strategies IJCAI 2017
Non-parametric Policy Search with Limited Information Loss JMLR 2017
Hierarchical Relative Entropy Policy Search JMLR 2016
Catching heuristics are optimal control policies NIPS 2016
Model-Free Trajectory Optimization for Reinforcement Learning ICML 2016
Learning of Non-Parametric Control Policies with High-Dimensional State Features AISTATS 2015
Model-Based Relative Entropy Stochastic Search NIPS 2015
Policy Evaluation with Temporal Differences: A Survey and Comparison JMLR 2014
Probabilistic Movement Primitives NIPS 2013
Hierarchical Relative Entropy Policy Search AISTATS 2012
Fitted Q-iteration by Advantage Weighted Regression NIPS 2008