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Deep Generative Symbolic Regression with Monte-Carlo-Tree-Search., , , and . ICML, volume 202 of Proceedings of Machine Learning Research, page 15655-15668. PMLR, (2023)End-to-end Symbolic Regression with Transformers, , , and . Advances in Neural Information Processing Systems, 35, page 10269--10281. Curran Associates, Inc., (2022)Direct then Diffuse: Incremental Unsupervised Skill Discovery for State Covering and Goal Reaching., , , , and . ICLR, OpenReview.net, (2022)SaLinA: Sequential Learning of Agents., , , , , and . CoRR, (2021)FACMAC: Factored Multi-Agent Centralised Policy Gradients., , , , , , and . NeurIPS, page 12208-12221. (2021)Efficient adaptation of reinforcement learning agents : from model-free exploration to symbolic world models. (Adaptation efficace des agents appris par renforcement : de l'exploration model-free aux modèles symboliques).. Sorbonne University, Paris, France, (2023)Direct then Diffuse: Incremental Unsupervised Skill Discovery for State Covering and Goal Reaching., , , and . CoRR, (2021)Deep symbolic regression for recurrence prediction., , , and . ICML, volume 162 of Proceedings of Machine Learning Research, page 4520-4536. PMLR, (2022)Privileged Information Dropout in Reinforcement Learning., , , , and . CoRR, (2020)Deep Multi-Agent Reinforcement Learning for Decentralized Continuous Cooperative Control., , , , , and . CoRR, (2020)