Gerhard Neumann
59 papers · 2008–2025 · 11 conferences · across top CS/AI conferences
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Conferences
ICLR (16)
NIPS (10)
JMLR (9)
CORL (8)
ICML (8)
AISTATS (2)
RSS (2)
CVPR (1)
ECCV (1)
IJCAI (1)
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Top co-authors
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