Toussaint, Marc

49 publications

TMLR 2025 Global Safe Sequential Learning via Efficient Knowledge Transfer Cen-You Li, Olaf Dünnbier, Marc Toussaint, Barbara Rakitsch, Christoph Zimmer

CoRL 2025 Meta-Optimization and Program Search Using Language Models for Task and Motion Planning Denis Shcherba, Eckart Cobo-Briesewitz, Cornelius V. Braun, Marc Toussaint

UAI 2025 Stein Variational Evolution Strategies Cornelius V. Braun, Robert Tjarko Lange, Marc Toussaint

ICML 2023 PaLM-E: An Embodied Multimodal Language Model Danny Driess, Fei Xia, Mehdi S. M. Sajjadi, Corey Lynch, Aakanksha Chowdhery, Brian Ichter, Ayzaan Wahid, Jonathan Tompson, Quan Vuong, Tianhe Yu, Wenlong Huang, Yevgen Chebotar, Pierre Sermanet, Daniel Duckworth, Sergey Levine, Vincent Vanhoucke, Karol Hausman, Marc Toussaint, Klaus Greff, Andy Zeng, Igor Mordatch, Pete Florence

CoRL 2022 Learning Multi-Object Dynamics with Compositional Neural Radiance Fields Danny Driess, Zhiao Huang, Yunzhu Li, Russ Tedrake, Marc Toussaint

NeurIPS 2022 Reinforcement Learning with Neural Radiance Fields Danny Driess, Ingmar Schubert, Pete Florence, Yunzhu Li, Marc Toussaint

ECML-PKDD 2021 Active Learning in Gaussian Process State Space Model Hon Sum Alec Yu, Dingling Yao, Christoph Zimmer, Marc Toussaint, Duy Nguyen-Tuong

CoRL 2021 Learning Models as Functionals of Signed-Distance Fields for Manipulation Planning Danny Driess, Jung-Su Ha, Marc Toussaint, Russ Tedrake

NeurIPS 2021 Learning to Execute: Efficient Learning of Universal Plan-Conditioned Policies in Robotics Ingmar Schubert, Danny Driess, Ozgur S. Oguz, Marc Toussaint

ICLR 2021 Plan-Based Relaxed Reward Shaping for Goal-Directed Tasks Ingmar Schubert, Ozgur S Oguz, Marc Toussaint

CoRL 2021 Structured Deep Generative Models for Sampling on Constraint Manifolds in Sequential Manipulation Joaquim Ortiz-Haro, Jung-Su Ha, Danny Driess, Marc Toussaint

CoRL 2020 Self-Supervised Learning of Scene-Graph Representations for Robotic Sequential Manipulation Planning Son Nguyen, Ozgur Oguz, Valentin Hartmann, Marc Toussaint

IJCAI 2019 Differentiable Physics and Stable Modes for Tool-Use and Manipulation Planning - Extended Abtract Marc Toussaint, Kelsey R. Allen, Kevin A. Smith, Joshua B. Tenenbaum

ICML 2019 Trajectory-Based Off-Policy Deep Reinforcement Learning Andreas Doerr, Michael Volpp, Marc Toussaint, Trimpe Sebastian, Christian Daniel

AAAI 2018 Bayesian Functional Optimization Ngo Anh Vien, Heiko Zimmermann, Marc Toussaint

ICML 2018 Probabilistic Recurrent State-Space Models Andreas Doerr, Christian Daniel, Martin Schiegg, Nguyen-Tuong Duy, Stefan Schaal, Marc Toussaint, Trimpe Sebastian

CoRL 2017 Optimizing Long-Term Predictions for Model-Based Policy Search Andreas Doerr, Christian Daniel, Duy Nguyen-Tuong, Alonso Marco, Stefan Schaal, Marc Toussaint, Sebastian Trimpe

IJCAI 2016 Policy Search in Reproducing Kernel Hilbert Space Ngo Anh Vien, Peter Englert, Marc Toussaint

AAAI 2015 Hierarchical Monte-Carlo Planning Ngo Anh Vien, Marc Toussaint

IJCAI 2015 Logic-Geometric Programming: An Optimization-Based Approach to Combined Task and Motion Planning Marc Toussaint

JAIR 2015 Probabilistic Inference Techniques for Scalable Multiagent Decision Making Akshat Kumar, Shlomo Zilberstein, Marc Toussaint

ECML-PKDD 2015 Safe Exploration for Active Learning with Gaussian Processes Jens Schreiter, Duy Nguyen-Tuong, Mona Eberts, Bastian Bischoff, Heiner Markert, Marc Toussaint

ICML 2014 Model-Based Relational RL When Object Existence Is Partially Observable Ngo Ahn Vien, Marc Toussaint

IJCAI 2013 Active Learning for Teaching a Robot Grounded Relational Symbols Johannes Kulick, Marc Toussaint, Tobias Lang, Manuel Lopes

IJCAI 2013 On Stochastic Optimal Control and Reinforcement Learning by Approximate Inference (Extended Abstract) Konrad Rawlik, Marc Toussaint, Sethu Vijayakumar

IJCAI 2013 Path Integral Control by Reproducing Kernel Hilbert Space Embedding Konrad Rawlik, Marc Toussaint, Sethu Vijayakumar

NeurIPS 2012 Exploration in Model-Based Reinforcement Learning by Empirically Estimating Learning Progress Manuel Lopes, Tobias Lang, Marc Toussaint, Pierre-yves Oudeyer

JMLR 2012 Exploration in Relational Domains for Model-Based Reinforcement Learning Tobias Lang, Marc Toussaint, Kristian Kersting

AISTATS 2012 Message-Passing Algorithms for MAP Estimation Using DC Programming Akshat Kumar, Shlomo Zilberstein, Marc Toussaint

ECML-PKDD 2011 Analyzing and Escaping Local Optima in Planning as Inference for Partially Observable Domains Pascal Poupart, Tobias Lang, Marc Toussaint

IJCAI 2011 Scalable Multiagent Planning Using Probabilistic Inference Akshat Kumar, Shlomo Zilberstein, Marc Toussaint

ICML 2011 Task Space Retrieval Using Inverse Feedback Control Nikolay Jetchev, Marc Toussaint

NeurIPS 2010 An Approximate Inference Approach to Temporal Optimization in Optimal Control Konrad Rawlik, Marc Toussaint, Sethu Vijayakumar

ECML-PKDD 2010 Exploration in Relational Worlds Tobias Lang, Marc Toussaint, Kristian Kersting

JAIR 2010 Planning with Noisy Probabilistic Relational Rules Tobias Lang, Marc Toussaint

ICML 2010 Probabilistic Backward and Forward Reasoning in Stochastic Relational Worlds Tobias Lang, Marc Toussaint

ICML 2009 Approximate Inference for Planning in Stochastic Relational Worlds Tobias Lang, Marc Toussaint

ICML 2009 Model-Free Reinforcement Learning as Mixture Learning Nikos Vlassis, Marc Toussaint

ICML 2009 Multi-Class Image Segmentation Using Conditional Random Fields and Global Classification Nils Plath, Marc Toussaint, Shinichi Nakajima

ECML-PKDD 2009 Relevance Grounding for Planning in Relational Domains Tobias Lang, Marc Toussaint

ICML 2009 Robot Trajectory Optimization Using Approximate Inference Marc Toussaint

ICML 2009 Trajectory Prediction: Learning to mAP Situations to Robot Trajectories Nikolay Jetchev, Marc Toussaint

UAI 2008 Hierarchical POMDP Controller Optimization by Likelihood Maximization Marc Toussaint, Laurent Charlin, Pascal Poupart

IJCAI 2007 A Primitive Based Generative Model to Infer Timing Information in Unpartitioned Handwriting Data Ben H. Williams, Marc Toussaint, Amos J. Storkey

NeurIPS 2007 Modelling Motion Primitives and Their Timing in Biologically Executed Movements Ben Williams, Marc Toussaint, Amos J. Storkey

ICML 2006 Probabilistic Inference for Solving Discrete and Continuous State Markov Decision Processes Marc Toussaint, Amos J. Storkey

IJCAI 2005 Learning Discontinuities for Switching Between Local Models Marc Toussaint, Sethu Vijayakumar

ICML 2005 Learning Discontinuities with Products-of-Sigmoids for Switching Between Local Models Marc Toussaint, Sethu Vijayakumar

NeurIPS 2003 Learning a World Model and Planning with a Self-Organizing, Dynamic Neural System Marc Toussaint