Parisotto, Emilio

17 publications

TMLR 2024 RoboCat: A Self-Improving Generalist Agent for Robotic Manipulation Konstantinos Bousmalis, Giulia Vezzani, Dushyant Rao, Coline Manon Devin, Alex X. Lee, Maria Bauza Villalonga, Todor Davchev, Yuxiang Zhou, Agrim Gupta, Akhil Raju, Antoine Laurens, Claudio Fantacci, Valentin Dalibard, Martina Zambelli, Murilo Fernandes Martins, Rugile Pevceviciute, Michiel Blokzijl, Misha Denil, Nathan Batchelor, Thomas Lampe, Emilio Parisotto, Konrad Zolna, Scott Reed, Sergio Gómez Colmenarejo, Jonathan Scholz, Abbas Abdolmaleki, Oliver Groth, Jean-Baptiste Regli, Oleg Sushkov, Thomas Rothörl, Jose Enrique Chen, Yusuf Aytar, David Barker, Joy Ortiz, Martin Riedmiller, Jost Tobias Springenberg, Raia Hadsell, Francesco Nori, Nicolas Heess

ICLR 2023 In-Context Reinforcement Learning with Algorithm Distillation Michael Laskin, Luyu Wang, Junhyuk Oh, Emilio Parisotto, Stephen Spencer, Richie Steigerwald, Dj Strouse, Steven Stenberg Hansen, Angelos Filos, Ethan Brooks, Maxime Gazeau, Himanshu Sahni, Satinder Singh, Volodymyr Mnih

NeurIPS 2023 Structured State Space Models for In-Context Reinforcement Learning Chris Lu, Yannick Schroecker, Albert Gu, Emilio Parisotto, Jakob Foerster, Satinder P. Singh, Feryal Behbahani

ICMLW 2023 Structured State Space Models for In-Context Reinforcement Learning Chris Lu, Yannick Schroecker, Albert Gu, Emilio Parisotto, Jakob Nicolaus Foerster, Satinder Singh, Feryal Behbahani

TMLR 2022 A Generalist Agent Scott Reed, Konrad Zolna, Emilio Parisotto, Sergio Gómez Colmenarejo, Alexander Novikov, Gabriel Barth-maron, Mai Giménez, Yury Sulsky, Jackie Kay, Jost Tobias Springenberg, Tom Eccles, Jake Bruce, Ali Razavi, Ashley Edwards, Nicolas Heess, Yutian Chen, Raia Hadsell, Oriol Vinyals, Mahyar Bordbar, Nando de Freitas

NeurIPSW 2022 In-Context Reinforcement Learning with Algorithm Distillation Michael Laskin, Luyu Wang, Junhyuk Oh, Emilio Parisotto, Stephen Spencer, Richie Steigerwald, Dj Strouse, Steven Stenberg Hansen, Angelos Filos, Ethan Brooks, Maxime Gazeau, Himanshu Sahni, Satinder Singh, Volodymyr Mnih

NeurIPSW 2022 In-Context Reinforcement Learning with Algorithm Distillation Michael Laskin, Luyu Wang, Junhyuk Oh, Emilio Parisotto, Stephen Spencer, Richie Steigerwald, Dj Strouse, Steven Stenberg Hansen, Angelos Filos, Ethan Brooks, Maxime Gazeau, Himanshu Sahni, Satinder Singh, Volodymyr Mnih

ICLR 2021 Efficient Transformers in Reinforcement Learning Using Actor-Learner Distillation Emilio Parisotto, Russ Salakhutdinov

ICML 2021 On Proximal Policy Optimization’s Heavy-Tailed Gradients Saurabh Garg, Joshua Zhanson, Emilio Parisotto, Adarsh Prasad, Zico Kolter, Zachary Lipton, Sivaraman Balakrishnan, Ruslan Salakhutdinov, Pradeep Ravikumar

ICML 2020 Stabilizing Transformers for Reinforcement Learning Emilio Parisotto, Francis Song, Jack Rae, Razvan Pascanu, Caglar Gulcehre, Siddhant Jayakumar, Max Jaderberg, Raphaël Lopez Kaufman, Aidan Clark, Seb Noury, Matthew Botvinick, Nicolas Heess, Raia Hadsell

ICLR 2018 Neural mAP: Structured Memory for Deep Reinforcement Learning Emilio Parisotto, Ruslan Salakhutdinov

ICLR 2018 Active Neural Localization Devendra Singh Chaplot, Emilio Parisotto, Ruslan Salakhutdinov

ICML 2018 Gated Path Planning Networks Lisa Lee, Emilio Parisotto, Devendra Singh Chaplot, Eric Xing, Ruslan Salakhutdinov

CVPRW 2018 Global Pose Estimation with an Attention-Based Recurrent Network Emilio Parisotto, Devendra Singh Chaplot, Jian Zhang, Ruslan Salakhutdinov

ICLR 2017 Neuro-Symbolic Program Synthesis Emilio Parisotto, Abdel-rahman Mohamed, Rishabh Singh, Lihong Li, Dengyong Zhou, Pushmeet Kohli

ICLR 2016 Actor-Mimic: Deep Multitask and Transfer Reinforcement Learning Emilio Parisotto, Lei Jimmy Ba, Ruslan Salakhutdinov

ICLR 2016 Generating Images from Captions with Attention Elman Mansimov, Emilio Parisotto, Lei Jimmy Ba, Ruslan Salakhutdinov