Neural fitted actor-critic. - Matthieu Zimmer; Yann Boniface; Alain Dutech (ESANN, 2016)

Developmental Reinforcement Learning through Sensorimotor Space Enlargement. - Matthieu Zimmer; Yann Boniface; Alain Dutech (ICDL-EPIROB, 2018)

Bootstrapping Q-Learning for Robotics From Neuro-Evolution Results. - Matthieu Zimmer; Stéphane Doncieux (IEEE Trans. Cogn. Dev. Syst., 2018)

Apprentissage par renforcement développemental. (Developmental reinforcement learning). - Matthieu Zimmer (2018)

An efficient reinforcement learning algorithm for learning deterministic policies in continuous domains. - Matthieu Zimmer; Paul Weng (DAI, 2019)

Exploiting the Sign of the Advantage Function to Learn Deterministic Policies in Continuous Domains. - Matthieu Zimmer; Paul Weng (IJCAI, 2019)

Invariant Transform Experience Replay. - Yijiong Lin; Jiancong Huang; Matthieu Zimmer; Juan Rojas 001; Paul Weng (CoRR, 2019)

Towards More Sample Efficiency in Reinforcement Learning with Data Augmentation. - Yijiong Lin; Jiancong Huang; Matthieu Zimmer; Juan Rojas 001; Paul Weng (CoRR, 2019)

Learning Fair Policies in Multi-Objective (Deep) Reinforcement Learning with Average and Discounted Rewards. - Umer Siddique; Paul Weng; Matthieu Zimmer (ICML, 2020)

Learning Fair Policies in Multiobjective (Deep) Reinforcement Learning with Average and Discounted Rewards. - Umer Siddique; Paul Weng; Matthieu Zimmer (CoRR, 2020)

Learning Fair Policies in Decentralized Cooperative Multi-Agent Reinforcement Learning. - Matthieu Zimmer; Umer Siddique; Paul Weng (CoRR, 2020)

Invariant Transform Experience Replay: Data Augmentation for Deep Reinforcement Learning. - Yijiong Lin; Jiancong Huang; Matthieu Zimmer; Yisheng Guan; Juan Rojas 001; Paul Weng (IEEE Robotics Autom. Lett., 2020)

Learning Fair Policies in Decentralized Cooperative Multi-Agent Reinforcement Learning. - Matthieu Zimmer; Claire Glanois; Umer Siddique; Paul Weng (ICML, 2021)

Neuro-Symbolic Hierarchical Rule Induction. - Claire Glanois; Xuening Feng; Zhaohui Jiang; Paul Weng; Matthieu Zimmer; Dong Li 016; Wulong Liu (CoRR, 2021)

Hyperparameter Auto-Tuning in Self-Supervised Robotic Learning. - Jiancong Huang; Juan Rojas 001; Matthieu Zimmer; Hongmin Wu; Yisheng Guan; Paul Weng (IEEE Robotics Autom. Lett., 2021)

Neuro-Symbolic Hierarchical Rule Induction. - Claire Glanois; Zhaohui Jiang; Xuening Feng; Paul Weng; Matthieu Zimmer; Dong Li 016; Wulong Liu; Jianye Hao (ICML, 2022)

Sample-Efficient Optimisation with Probabilistic Transformer Surrogates. - Alexandre Maraval; Matthieu Zimmer; Antoine Grosnit; Rasul Tutunov; Jun Wang 012; Haitham Bou-Ammar (CoRR, 2022)

Lightweight Structural Choices Operator for Technology Mapping. - Antoine Grosnit; Matthieu Zimmer; Rasul Tutunov; Xing Li; Lei Chen 031; Fan Yang; Mingxuan Yuan; Haitham Bou-Ammar (DAC, 2023)

Automatic Unit Test Data Generation and Actor-Critic Reinforcement Learning for Code Synthesis. - Philip John Gorinski; Matthieu Zimmer; Gerasimos Lampouras; Derrick-Goh-Xin Deik; Ignacio Iacobacci (EMNLP (Findings), 2023)

End-to-End Meta-Bayesian Optimisation with Transformer Neural Processes. - Alexandre Maraval; Matthieu Zimmer; Antoine Grosnit; Haitham Bou-Ammar (NeurIPS, 2023)

Pangu-Agent: A Fine-Tunable Generalist Agent with Structured Reasoning. - Filippos Christianos; Georgios Papoudakis; Matthieu Zimmer; Thomas Coste; Zhihao Wu; Jingxuan Chen; Khyati Khandelwal; James Doran; Xidong Feng; Jiacheng Liu; Zheng Xiong; Yicheng Luo; et al. (CoRR, 2023)

Differentiable Logic Machines. - Matthieu Zimmer; Xuening Feng; Claire Glanois; Zhaohui Jiang; Jianyi Zhang; Paul Weng; Dong Li 016; Jianye Hao; Wulong Liu (Trans. Mach. Learn. Res., 2023)

Distilling Morphology-Conditioned Hypernetworks for Efficient Universal Morphology Control. - Zheng Xiong; Risto Vuorio; Jacob Beck; Matthieu Zimmer; Kun Shao; Shimon Whiteson (ICML, 2024)

ROS-LLM: A ROS framework for embodied AI with task feedback and structured reasoning. - Christopher E. Mower; Yuhui Wan; Hongzhan Yu; Antoine Grosnit; Jonas Gonzalez-Billandon; Matthieu Zimmer; Jinlong Wang; Xinyu Zhang; Yao Zhao; Anbang Zhai; Puze Liu; Davide Tateo; et al. (CoRR, 2024)

A survey on interpretable reinforcement learning. - Claire Glanois; Paul Weng; Matthieu Zimmer; Dong Li 016; Tianpei Yang; Jianye Hao; Wulong Liu (Mach. Learn., 2024)

Mixture of Attentions For Speculative Decoding. - Matthieu Zimmer; Milan Gritta; Gerasimos Lampouras; Haitham Bou-Ammar; Jun Wang 012 (ICLR, 2025)

Almost Surely Safe Alignment of Large Language Models at Inference-Time. - Xiaotong Ji; Shyam Sundhar Ramesh; Matthieu Zimmer; Ilija Bogunovic; Jun Wang 012; Haitham Bou-Ammar (CoRR, 2025)

Bourbaki: Self-Generated and Goal-Conditioned MDPs for Theorem Proving. - Matthieu Zimmer; Xiaotong Ji; Rasul Tutunov; Anthony Bordg; Jun Wang 012; Haitham Bou-Ammar (CoRR, 2025)