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Martin Riedmiller

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

Authors are matched by name, so researchers who share a name ("Yang Liu", "Wei Wang") appear as a single profile and their paper counts, venues and achievements are combined. How identity is handled.

Achievements

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+17 more ↓ πŸ—ΊοΈ Taxonomy Completionist (45) πŸƒ Academic Marathon Β· Half 🌍 Conference Polyglot Β· Silver πŸŒ‰ Interdisciplinary Bridge Β· Silver 🐣 Hot Topic Early Bird
🌱 Topic Pioneer πŸ‘‘ Triple Crown πŸ”¬ Deep Specialist (15) 🌟 Keyword Trendsetter Combo (3) πŸ‘₯ Mega-Team Β· Squad 🧬 Topic Evolution 🀝 Dynamic Duo (21) 🧭 Keyword Pioneer πŸ† Keyword Champion (3) 🌈 Renaissance Researcher (5) πŸ”₯ Unstoppable Β· Bronze ❓ The Questioner ⚑ Prolific Year Β· Productive πŸš€ Conference Pioneer πŸ’Ž Century Club Β· Bronze πŸ“ˆ Trend Setter πŸ—ƒοΈ Keyword Collector (143)

Venues

ICLR (9) CoRL (8) ICML (6) NeurIPS (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)

Research topics

Reinforcement Learning (26) Machine Learning (23) Methods (21) Applications (15) Artificial Intelligence (14) Core AI (12) Learning Types Β· Machine Learning (12) Optimization & Theory (8) Robotics (5) Core Methods (5) Deep Learning (4) Capabilities (4) Learning Paradigms (4) Learning Types Β· Deep Learning (4) Application Areas (2)

Keywords

continuous control (8) policy optimization (7) reinforcement learning (6) off-policy learning (5) deep reinforcement learning (4) offline reinforcement learning (3) transfer learning (3) multi-task learning (3) data efficiency (3) robot manipulation (3) optimal control (3) imitation learning (2) experience replay (2) language model (2) maximum a posteriori (2) model-based reinforcement learning (2) sequence modeling (1) online learning (1) multi-agent reinforcement learning (1) model-based planning (1)

Papers

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