Valentin Dalibard

20 papers A* 4A 1Misc 1Journal 13Unranked 1
YearRankTypeTitle / Venue / Authors
2025 A* conf
DemoStart: Demonstration-Led Auto-Curriculum Applied to Sim-to-Real with Multi-Fingered Robots.
ICRA
Maria Bauzá, Jose Enriaue Chen, Valentin Dalibard, Nimrod Gileadi, Roland Hafner, Murilo F. Martins, Joss Moore, Rugile Pevceviciute, Antoine Laurens, Dushyant Rao, Martina Zambelli, Martin A. Riedmiller, Jon Scholz, Konstantinos Bousmalis, Francesco Nori, Nicolas Heess
2024 J jnl
DemoStart: Demonstration-led auto-curriculum applied to sim-to-real with multi-fingered robots.
CoRR
Maria Bauzá, José Enrique Chen, Valentin Dalibard, Nimrod Gileadi, Roland Hafner, Murilo F. Martins, Joss Moore, Rugile Pevceviciute, Antoine Laurens, Dushyant Rao, Martina Zambelli, Martin A. Riedmiller, Jon Scholz, Konstantinos Bousmalis, Francesco Nori, Nicolas Heess
2024 J jnl
RoboCat: A Self-Improving Generalist Agent for Robotic Manipulation.
Trans. Mach. Learn. Res.
Konstantinos Bousmalis, Giulia Vezzani, Dushyant Rao, Coline Manon Devin, Alex X. Lee, Maria Bauzá 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 E. Reed, Sergio Gómez Colmenarejo, Jon Scholz, Abbas Abdolmaleki, Oliver Groth, Jean-Baptiste Regli, Oleg Sushkov, Thomas Rothörl, José Enrique Chen, Yusuf Aytar, Dave Barker, Joy Ortiz, Martin A. Riedmiller, Jost Tobias Springenberg, Raia Hadsell, Francesco Nori, Nicolas Heess
2023 A conf
Discovering Attention-Based Genetic Algorithms via Meta-Black-Box Optimization.
GECCO
Robert Tjarko Lange, Tom Schaul, Yutian Chen, Chris Lu, Tom Zahavy, Valentin Dalibard, Sebastian Flennerhag
2023 J jnl
Discovering Attention-Based Genetic Algorithms via Meta-Black-Box Optimization.
CoRR
Robert Tjarko Lange, Tom Schaul, Yutian Chen, Chris Lu, Tom Zahavy, Valentin Dalibard, Sebastian Flennerhag
2023 — conf
Discovering Evolution Strategies via Meta-Black-Box Optimization.
GECCO Companion
Robert Tjarko Lange, Tom Schaul, Yutian Chen, Tom Zahavy, Valentin Dalibard, Chris Lu, Satinder Singh, Sebastian Flennerhag
2023 A* conf
Discovering Evolution Strategies via Meta-Black-Box Optimization.
ICLR
Robert Tjarko Lange, Tom Schaul, Yutian Chen, Tom Zahavy, Valentin Dalibard, Chris Lu, Satinder Singh, Sebastian Flennerhag
2023 J jnl
RoboCat: A Self-Improving Foundation Agent for Robotic Manipulation.
CoRR
Konstantinos Bousmalis, Giulia Vezzani, Dushyant Rao, Coline Devin, Alex X. Lee, Maria Bauzá, Todor Davchev, Yuxiang Zhou, Agrim Gupta, Akhil Raju, Antoine Laurens, Claudio Fantacci, Valentin Dalibard, Martina Zambelli, Murilo F. Martins, Rugile Pevceviciute, Michiel Blokzijl, Misha Denil, Nathan Batchelor, Thomas Lampe, Emilio Parisotto, Konrad Zolna, Scott E. Reed, Sergio Gómez Colmenarejo, Jon Scholz, Abbas Abdolmaleki, Oliver Groth, Jean-Baptiste Regli, Oleg Sushkov, Thomas Rothörl, José Enrique Chen, Yusuf Aytar, Dave Barker, Joy Ortiz, Martin A. Riedmiller, Jost Tobias Springenberg, Raia Hadsell, Francesco Nori, Nicolas Heess
2021 J jnl
Faster Improvement Rate Population Based Training.
CoRR
Valentin Dalibard, Max Jaderberg
2021 J jnl
Open-Ended Learning Leads to Generally Capable Agents.
CoRR
Open Ended Learning Team, Adam Stooke, Anuj Mahajan, Catarina Barros, Charlie Deck, Jakob Bauer, Jakub Sygnowski, Maja Trebacz, Max Jaderberg, Michaël Mathieu, Nat McAleese, Nathalie Bradley-Schmieg, Nathaniel Wong, Nicolas Porcel, Roberta Raileanu, Steph Hughes-Fitt, Valentin Dalibard, Wojciech Marian Czarnecki
2021 J jnl
Rapid training of deep neural networks without skip connections or normalization layers using Deep Kernel Shaping.
CoRR
James Martens, Andy Ballard, Guillaume Desjardins, Grzegorz Swirszcz, Valentin Dalibard, Jascha Sohl-Dickstein, Samuel S. Schoenholz
2020 J jnl
Perception-Prediction-Reaction Agents for Deep Reinforcement Learning.
CoRR
Adam Stooke, Valentin Dalibard, Siddhant M. Jayakumar, Wojciech M. Czarnecki, Max Jaderberg
2019 A* conf
A Generalized Framework for Population Based Training.
KDD
Ang Li, Ola Spyra, Sagi Perel, Valentin Dalibard, Max Jaderberg, Chenjie Gu, David Budden, Tim Harley, Pramod Gupta
2019 J jnl
A Generalized Framework for Population Based Training.
CoRR
Ang Li, Ola Spyra, Sagi Perel, Valentin Dalibard, Max Jaderberg, Chenjie Gu, David Budden, Tim Harley, Pramod Gupta
2019 J jnl
Grandmaster level in StarCraft II using multi-agent reinforcement learning.
Nat.
Oriol Vinyals, Igor Babuschkin, Wojciech M. Czarnecki, Michaël Mathieu, Andrew Dudzik, Junyoung Chung, David H. Choi, Richard Powell, Timo Ewalds, Petko Georgiev, Junhyuk Oh, Dan Horgan, Manuel Kroiss, Ivo Danihelka, Aja Huang, Laurent Sifre, Trevor Cai, John P. Agapiou, Max Jaderberg, Alexander Sasha Vezhnevets, Rémi Leblond, Tobias Pohlen, Valentin Dalibard, David Budden, Yury Sulsky, James Molloy, Tom Le Paine, Çaglar Gülçehre, Ziyu Wang, Tobias Pfaff, Yuhuai Wu, Roman Ring, Dani Yogatama, Dario Wünsch, Katrina McKinney, Oliver Smith, Tom Schaul, Timothy P. Lillicrap, Koray Kavukcuoglu, Demis Hassabis, Chris Apps, David Silver
2017 A* conf
BOAT: Building Auto-Tuners with Structured Bayesian Optimization.
WWW
Valentin Dalibard, Michael Schaarschmidt, Eiko Yoneki
2017 J jnl
Population Based Training of Neural Networks.
CoRR
Max Jaderberg, Valentin Dalibard, Simon Osindero, Wojciech M. Czarnecki, Jeff Donahue, Ali Razavi, Oriol Vinyals, Tim Green, Iain Dunning, Karen Simonyan, Chrisantha Fernando, Koray Kavukcuoglu
2016 J jnl
Learning Runtime Parameters in Computer Systems with Delayed Experience Injection.
CoRR
Michael Schaarschmidt, Felix Gessert, Valentin Dalibard, Eiko Yoneki
2016 J jnl
Tuning the Scheduling of Distributed Stochastic Gradient Descent with Bayesian Optimization.
CoRR
Valentin Dalibard, Michael Schaarschmidt, Eiko Yoneki
2014 Misc conf
PrefEdge: SSD Prefetcher for Large-Scale Graph Traversal.
SYSTOR
Karthik Nilakant, Valentin Dalibard, Amitabha Roy, Eiko Yoneki