← Authors

Marc Toussaint

30 papers · 2007–2025 · 9 conferences · across top CS/AI conferences

Achievements

🌍 Conference Polyglot (9) 🐝 Cross-Pollinator (12) 🌈 Renaissance Researcher (5) πŸŒ‰ Interdisciplinary Bridge πŸƒ Academic Marathon (18) πŸ—ΊοΈ Taxonomy Completionist (11) 🧭 Keyword Pioneer 🐣 Hot Topic Early Bird 🌟 Keyword Trendsetter Combo (3) πŸ† Keyword Champion (3) 🧬 Topic Evolution πŸ‘₯ Mega-Team (22) πŸ“ˆ Trend Setter πŸ—ƒοΈ Keyword Collector (105) πŸ’Ž Century Club (30) ⚑ Prolific Year (5) πŸ”₯ Unstoppable (6) πŸš€ Conference Pioneer

Conferences

IJCAI (6) RSS (6) CORL (5) NIPS (5) ICML (4) AISTATS (1) ICLR (1) JMLR (1) UAI (1)

Top co-authors

Danny Driess (7) Sethu Vijayakumar (5) Konrad Rawlik (4) Jung-Su Ha (3) Andreas Doerr (3) Ingmar Schubert (3) Tobias Lang (3) Peter Englert (2) Yunzhu Li (2) Stefan Schaal (2)

Research topics

Robotics (1)

Keywords

reinforcement learning (4) model-based reinforcement learning (3) approximate inference (3) manipulation planning (3) task and motion planning (3) optimal control (3) motion planning (2) variational inference (2) robotic manipulation (2) sequential manipulation (2) robot manipulation (2) policy learning (2) neural radiance field (2) probabilistic modeling (2) structured prediction (1) bayesian inference (1) sample efficiency (1) policy optimization (1) motion synthesis (1) imitation learning (1)

Papers

Meta-Optimization and Program Search using Language Models for Task and Motion Planning CORL 2025
Stein Variational Evolution Strategies UAI 2025
PaLM-E: An Embodied Multimodal Language Model ICML 2023
Reinforcement Learning with Neural Radiance Fields NIPS 2022
Learning Multi-Object Dynamics with Compositional Neural Radiance Fields CORL 2022
Structured deep generative models for sampling on constraint manifolds in sequential manipulation CORL 2021
Plan-Based Relaxed Reward Shaping for Goal-Directed Tasks ICLR 2021
Learning Models as Functionals of Signed-Distance Fields for Manipulation Planning CORL 2021
Learning to Execute: Efficient Learning of Universal Plan-Conditioned Policies in Robotics NIPS 2021
Deep Visual Reasoning: Learning to Predict Action Sequences for Task and Motion Planning from an Initial Scene Image RSS 2020
Self-Supervised Learning of Scene-Graph Representations for Robotic Sequential Manipulation Planning CORL 2020
Trajectory-Based Off-Policy Deep Reinforcement Learning ICML 2019
Differentiable Physics and Stable Modes for Tool-Use and Manipulation Planning - Extended Abtract IJCAI 2019
Probabilistic Recurrent State-Space Models ICML 2018
Differentiable Physics and Stable Modes for Tool-Use and Manipulation Planning RSS 2018
Policy Search in Reproducing Kernel Hilbert Space IJCAI 2016
Combined Optimization and Reinforcement Learning for Manipulation Skills RSS 2016
Direct Loss Minimization Inverse Optimal Control RSS 2015
Logic-Geometric Programming: An Optimization-Based Approach to Combined Task and Motion Planning IJCAI 2015
Model-Based Relational RL When Object Existence is Partially Observable ICML 2014
Active Learning for Teaching a Robot Grounded Relational Symbols IJCAI 2013
Path Integral Control by Reproducing Kernel Hilbert Space Embedding IJCAI 2013
On Stochastic Optimal Control and Reinforcement Learning by Approximate Inference (Extended Abstract) IJCAI 2013
Hierarchical Motion Planning in Topological Representations RSS 2012
Exploration in Relational Domains for Model-based Reinforcement Learning JMLR 2012
On Stochastic Optimal Control and Reinforcement Learning by Approximate Inference RSS 2012
Message-Passing Algorithms for MAP Estimation Using DC Programming AISTATS 2012
Exploration in Model-based Reinforcement Learning by Empirically Estimating Learning Progress NIPS 2012
An Approximate Inference Approach to Temporal Optimization in Optimal Control NIPS 2010
Modelling motion primitives and their timing in biologically executed movements NIPS 2007