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ORCIDH. Francis Song
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2020 – today
- 2022
[j3]Siqi Liu
, Guy Lever, Zhe Wang, Josh Merel, S. M. Ali Eslami, Daniel Hennes, Wojciech M. Czarnecki, Yuval Tassa, Shayegan Omidshafiei, Abbas Abdolmaleki, Noah Y. Siegel, Leonard Hasenclever, Luke Marris, Saran Tunyasuvunakool, H. Francis Song, Markus Wulfmeier, Paul Muller, Tuomas Haarnoja, Brendan D. Tracey, Karl Tuyls, Thore Graepel, Nicolas Heess:
From motor control to team play in simulated humanoid football. Sci. Robotics 7(69) (2022)- [c8]Ethan Perez, Saffron Huang, H. Francis Song, Trevor Cai, Roman Ring, John Aslanides, Amelia Glaese, Nat McAleese, Geoffrey Irving:
Red Teaming Language Models with Language Models. EMNLP 2022: 3419-3448 - [d1]Siqi Liu, Guy Lever, Zhe Wang, Josh Merel, S. M. Ali Eslami, Daniel Hennes, Wojciech Czarnecki, Yuval Tassa, Shayegan Omidshafiei, Abbas Abdolmaleki, Noah Y. Siegel, Leonard Hasenclever, Luke Marris, Saran Tunyasuvunakool, H. Francis Song, Markus Wulfmeier, Paul Muller, Tuomas Haarnoja, Brendan D. Tracey, Karl Tuyls, Thore Graepel, Nicolas Heess:
Figure Data for the paper "From Motor Control to Team Play in Simulated Humanoid Football". Zenodo, 2022
- [i16]Ethan Perez, Saffron Huang, H. Francis Song, Trevor Cai, Roman Ring, John Aslanides, Amelia Glaese, Nat McAleese, Geoffrey Irving:
Red Teaming Language Models with Language Models. CoRR abs/2202.03286 (2022) - [i15]Jacob Menick, Maja Trebacz, Vladimir Mikulik, John Aslanides, H. Francis Song, Martin J. Chadwick, Mia Glaese, Susannah Young, Lucy Campbell-Gillingham, Geoffrey Irving, Nat McAleese:
Teaching language models to support answers with verified quotes. CoRR abs/2203.11147 (2022) - [i14]Jonathan Uesato, Nate Kushman, Ramana Kumar, H. Francis Song, Noah Y. Siegel, Lisa Wang, Antonia Creswell, Geoffrey Irving, Irina Higgins:
Solving math word problems with process- and outcome-based feedback. CoRR abs/2211.14275 (2022) - 2021
- [c7]Jane Wang, Michael King, Nicolas Porcel, Zeb Kurth-Nelson, Tina Zhu, Charles Deck, Peter Choy, Mary Cassin, Malcolm Reynolds, H. Francis Song, Gavin Buttimore, David P. Reichert, Neil C. Rabinowitz, Loic Matthey, Demis Hassabis, Alexander Lerchner, Matt M. Botvinick:
Alchemy: A benchmark and analysis toolkit for meta-reinforcement learning agents. NeurIPS Datasets and Benchmarks 2021 - [i13]Jane X. Wang, Michael King, Nicolas Porcel, Zeb Kurth-Nelson, Tina Zhu, Charlie Deck, Peter Choy, Mary Cassin, Malcolm Reynolds, H. Francis Song, Gavin Buttimore, David P. Reichert, Neil C. Rabinowitz, Loic Matthey, Demis Hassabis, Alexander Lerchner, Matthew M. Botvinick:
Alchemy: A structured task distribution for meta-reinforcement learning. CoRR abs/2102.02926 (2021) - [i12]David Raposo, Samuel Ritter, Adam Santoro, Greg Wayne, Theophane Weber, Matt M. Botvinick, Hado van Hasselt, H. Francis Song:
Synthetic Returns for Long-Term Credit Assignment. CoRR abs/2102.12425 (2021) - [i11]Siqi Liu, Guy Lever, Zhe Wang, Josh Merel, S. M. Ali Eslami, Daniel Hennes, Wojciech M. Czarnecki, Yuval Tassa, Shayegan Omidshafiei, Abbas Abdolmaleki, Noah Y. Siegel, Leonard Hasenclever, Luke Marris, Saran Tunyasuvunakool, H. Francis Song, Markus Wulfmeier, Paul Muller, Tuomas Haarnoja, Brendan D. Tracey, Karl Tuyls, Thore Graepel, Nicolas Heess:
From Motor Control to Team Play in Simulated Humanoid Football. CoRR abs/2105.12196 (2021) - [i10]Jack W. Rae, Sebastian Borgeaud, Trevor Cai, Katie Millican, Jordan Hoffmann, H. Francis Song, John Aslanides, Sarah Henderson, Roman Ring, Susannah Young, Eliza Rutherford, Tom Hennigan, Jacob Menick, Albin Cassirer, Richard Powell, George van den Driessche, Lisa Anne Hendricks, Maribeth Rauh, Po-Sen Huang, Amelia Glaese, Johannes Welbl, Sumanth Dathathri, Saffron Huang, Jonathan Uesato, John Mellor, Irina Higgins, Antonia Creswell, Nat McAleese, Amy Wu, Erich Elsen, Siddhant M. Jayakumar, Elena Buchatskaya, David Budden, Esme Sutherland, Karen Simonyan, Michela Paganini, Laurent Sifre, Lena Martens, Xiang Lorraine Li, Adhiguna Kuncoro, Aida Nematzadeh, Elena Gribovskaya, Domenic Donato, Angeliki Lazaridou, Arthur Mensch, Jean-Baptiste Lespiau, Maria Tsimpoukelli, Nikolai Grigorev, Doug Fritz, Thibault Sottiaux, Mantas Pajarskas, Toby Pohlen, Zhitao Gong, Daniel Toyama, Cyprien de Masson d'Autume, Yujia Li, Tayfun Terzi, Vladimir Mikulik, Igor Babuschkin, Aidan Clark, Diego de Las Casas, Aurelia Guy, Chris Jones, James Bradbury, Matthew J. Johnson, Blake A. Hechtman, Laura Weidinger, Iason Gabriel, William Isaac, Edward Lockhart, Simon Osindero, Laura Rimell, Chris Dyer, Oriol Vinyals, Kareem Ayoub, Jeff Stanway, Lorrayne Bennett, Demis Hassabis, Koray Kavukcuoglu, Geoffrey Irving:
Scaling Language Models: Methods, Analysis & Insights from Training Gopher. CoRR abs/2112.11446 (2021) - 2020
- [j2]Nolan Bard, Jakob N. Foerster, Sarath Chandar, Neil Burch, Marc Lanctot, H. Francis Song, Emilio Parisotto, Vincent Dumoulin, Subhodeep Moitra, Edward Hughes, Iain Dunning, Shibl Mourad, Hugo Larochelle, Marc G. Bellemare, Michael Bowling:
The Hanabi challenge: A new frontier for AI research. Artif. Intell. 280: 103216 (2020) - [c6]H. Francis Song, Abbas Abdolmaleki, Jost Tobias Springenberg, Aidan Clark, Hubert Soyer, Jack W. Rae, Seb Noury, Arun Ahuja, Siqi Liu, Dhruva Tirumala, Nicolas Heess, Dan Belov, Martin A. Riedmiller, Matthew M. Botvinick:
V-MPO: On-Policy Maximum a Posteriori Policy Optimization for Discrete and Continuous Control. ICLR 2020 - [c5]Abbas Abdolmaleki, Sandy H. Huang, Leonard Hasenclever, Michael Neunert, H. Francis Song, Martina Zambelli, Murilo F. Martins, Nicolas Heess, Raia Hadsell, Martin A. Riedmiller:
A distributional view on multi-objective policy optimization. ICML 2020: 11-22 - [c4]Emilio Parisotto, H. Francis Song, Jack W. Rae, Razvan Pascanu, Çaglar Gülçehre, Siddhant M. Jayakumar, Max Jaderberg, Raphaël Lopez Kaufman, Aidan Clark, Seb Noury, Matthew M. Botvinick, Nicolas Heess, Raia Hadsell:
Stabilizing Transformers for Reinforcement Learning. ICML 2020: 7487-7498 - [i9]Abbas Abdolmaleki, Sandy H. Huang, Leonard Hasenclever, Michael Neunert, H. Francis Song, Martina Zambelli, Murilo F. Martins, Nicolas Heess, Raia Hadsell, Martin A. Riedmiller:
A Distributional View on Multi-Objective Policy Optimization. CoRR abs/2005.07513 (2020)
2010 – 2019
- 2019
- [c3]Andrea Tacchetti, H. Francis Song, Pedro A. M. Mediano, Vinícius Flores Zambaldi, János Kramár, Neil C. Rabinowitz, Thore Graepel, Matthew M. Botvinick, Peter W. Battaglia:
Relational Forward Models for Multi-Agent Learning. ICLR (Poster) 2019 - [c2]Jakob N. Foerster, H. Francis Song, Edward Hughes, Neil Burch, Iain Dunning, Shimon Whiteson, Matthew M. Botvinick, Michael Bowling:
Bayesian Action Decoder for Deep Multi-Agent Reinforcement Learning. ICML 2019: 1942-1951 - [i8]Nolan Bard, Jakob N. Foerster, Sarath Chandar, Neil Burch, Marc Lanctot, H. Francis Song, Emilio Parisotto, Vincent Dumoulin, Subhodeep Moitra, Edward Hughes, Iain Dunning, Shibl Mourad, Hugo Larochelle, Marc G. Bellemare, Michael Bowling:
The Hanabi Challenge: A New Frontier for AI Research. CoRR abs/1902.00506 (2019) - [i7]H. Francis Song, Abbas Abdolmaleki, Jost Tobias Springenberg, Aidan Clark, Hubert Soyer, Jack W. Rae, Seb Noury, Arun Ahuja, Siqi Liu, Dhruva Tirumala, Nicolas Heess, Dan Belov, Martin A. Riedmiller, Matthew M. Botvinick:
V-MPO: On-Policy Maximum a Posteriori Policy Optimization for Discrete and Continuous Control. CoRR abs/1909.12238 (2019) - [i6]Emilio Parisotto, H. Francis Song, Jack W. Rae, Razvan Pascanu, Çaglar Gülçehre, Siddhant M. Jayakumar, Max Jaderberg, Raphael Lopez Kaufman, Aidan Clark, Seb Noury, Matthew M. Botvinick, Nicolas Heess, Raia Hadsell:
Stabilizing Transformers for Reinforcement Learning. CoRR abs/1910.06764 (2019) - 2018
- [c1]Neil C. Rabinowitz, Frank Perbet, H. Francis Song, Chiyuan Zhang, S. M. Ali Eslami, Matthew M. Botvinick:
Machine Theory of Mind. ICML 2018: 4215-4224 - [i5]Neil C. Rabinowitz, Frank Perbet, H. Francis Song, Chiyuan Zhang, S. M. Ali Eslami, Matthew M. Botvinick:
Machine Theory of Mind. CoRR abs/1802.07740 (2018) - [i4]Peter W. Battaglia, Jessica B. Hamrick, Victor Bapst, Alvaro Sanchez-Gonzalez, Vinícius Flores Zambaldi, Mateusz Malinowski, Andrea Tacchetti, David Raposo, Adam Santoro, Ryan Faulkner, Çaglar Gülçehre, H. Francis Song, Andrew J. Ballard, Justin Gilmer, George E. Dahl, Ashish Vaswani, Kelsey R. Allen, Charles Nash, Victoria Langston, Chris Dyer, Nicolas Heess, Daan Wierstra, Pushmeet Kohli, Matthew M. Botvinick, Oriol Vinyals, Yujia Li, Razvan Pascanu:
Relational inductive biases, deep learning, and graph networks. CoRR abs/1806.01261 (2018) - [i3]Andrea Tacchetti, H. Francis Song, Pedro A. M. Mediano, Vinícius Flores Zambaldi, Neil C. Rabinowitz, Thore Graepel, Matthew M. Botvinick, Peter W. Battaglia:
Relational Forward Models for Multi-Agent Learning. CoRR abs/1809.11044 (2018) - [i2]Jakob N. Foerster, H. Francis Song, Edward Hughes, Neil Burch, Iain Dunning, Shimon Whiteson, Matthew M. Botvinick, Michael Bowling:
Bayesian Action Decoder for Deep Multi-Agent Reinforcement Learning. CoRR abs/1811.01458 (2018) - 2016
- [j1]H. Francis Song, Guangyu R. Yang, Xiao-Jing Wang:
Training Excitatory-Inhibitory Recurrent Neural Networks for Cognitive Tasks: A Simple and Flexible Framework. PLoS Comput. Biol. 12(2) (2016) - 2014
- [i1]H. Francis Song, Xiao-Jing Wang:
A simple, distance-dependent formulation of the Watts-Strogatz model for directed and undirected small-world networks. CoRR abs/1408.4461 (2014)
Coauthor Index
aka: Matthew M. Botvinick
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