← Authors

Martin Riedmiller

30 papers · 2014–2025 · 6 conferences · across top CS/AI conferences

Achievements

🧭 Keyword Pioneer 🌈 Renaissance Researcher (7) 🐝 Cross-Pollinator (13) πŸƒ Academic Marathon (11) 🌍 Conference Polyglot (6) πŸŒ‰ Interdisciplinary Bridge 🐣 Hot Topic Early Bird πŸ—ΊοΈ Taxonomy Completionist (10) 🌟 Keyword Trendsetter Combo (3) 🀝 Dynamic Duo (21) πŸ‘₯ Mega-Team (21) πŸ‘‘ Triple Crown 🌱 Topic Pioneer πŸ”¬ Deep Specialist (11) 🧬 Topic Evolution πŸ—ƒοΈ Keyword Collector (98) πŸ“ˆ Trend Setter πŸ’Ž Century Club (30) πŸš€ Conference Pioneer ⚑ Prolific Year (5) πŸ”₯ Unstoppable (8) ❓ The Questioner

Conferences

ICLR (9) CORL (8) ICML (6) NIPS (4) RSS (2) L4DC (1)

Top co-authors

Nicolas Heess (21) Jost Tobias Springenberg (17) Abbas Abdolmaleki (16) Michael Neunert (12) Thomas Lampe (12) Roland Hafner (11) Markus Wulfmeier (10) Arunkumar Byravan (6) Tim Hertweck (6) Sandy Huang (5)

Keywords

reinforcement learning (5) off-policy learning (4) policy optimization (3) offline reinforcement learning (3) optimal control (3) multi-task learning (3) robot manipulation (3) imitation learning (2) continuous control (2) model-based reinforcement learning (2) transfer learning (2) deep reinforcement learning (2) robotic manipulation (1) sim-to-real transfer (1) image classification (1) sequence generation (1) online learning (1) policy learning (1) sequence modeling (1) preference learning (1)

Papers

Learning from negative feedback, or positive feedback or both ICLR 2025
Imitating Language via Scalable Inverse Reinforcement Learning NIPS 2024
Learning Robot Soccer from Egocentric Vision with Deep Reinforcement Learning CORL 2024
Offline Actor-Critic Reinforcement Learning Scales to Large Models ICML 2024
Replay across Experiments: A Natural Extension of Off-Policy RL ICLR 2024
Real-world fluid directed rigid body control via deep reinforcement learning L4DC 2024
Solving Continuous Control via Q-learning ICLR 2023
Evaluating Model-Based Planning and Planner Amortization for Continuous Control ICLR 2022
A Constrained Multi-Objective Reinforcement Learning Framework CORL 2021
Data-efficient Hindsight Off-policy Option Learning ICML 2021
Is Bang-Bang Control All You Need? Solving Continuous Control with Bernoulli Policies NIPS 2021
Beyond Pick-and-Place: Tackling Robotic Stacking of Diverse Shapes CORL 2021
Towards Real Robot Learning in the Wild: A Case Study in Bipedal Locomotion CORL 2021
Collect & Infer - a fresh look at data-efficient Reinforcement Learning CORL 2021
Compositional Transfer in Hierarchical Reinforcement Learning RSS 2020
Towards General and Autonomous Learning of Core Skills: A Case Study in Locomotion CORL 2020
Keep Doing What Worked: Behavior Modelling Priors for Offline Reinforcement Learning ICLR 2020
Robust Reinforcement Learning for Continuous Control with Model Misspecification ICLR 2020
V-MPO: On-Policy Maximum a Posteriori Policy Optimization for Discrete and Continuous Control ICLR 2020
A distributional view on multi-objective policy optimization ICML 2020
Simultaneously Learning Vision and Feature-Based Control Policies for Real-World Ball-In-A-Cup RSS 2019
Imagined Value Gradients: Model-Based Policy Optimization with Tranferable Latent Dynamics Models CORL 2019
Continuous-Discrete Reinforcement Learning for Hybrid Control in Robotics CORL 2019
Learning an Embedding Space for Transferable Robot Skills ICLR 2018
Learning by Playing Solving Sparse Reward Tasks from Scratch ICML 2018
Graph Networks as Learnable Physics Engines for Inference and Control ICML 2018
Maximum a Posteriori Policy Optimisation ICLR 2018
Embed to Control: A Locally Linear Latent Dynamics Model for Control from Raw Images NIPS 2015
Deterministic Policy Gradient Algorithms ICML 2014
Discriminative Unsupervised Feature Learning with Convolutional Neural Networks NIPS 2014