A simple, distance-dependent formulation of the Watts-Strogatz model for directed and undirected small-world networks. - H. Francis Song; Xiao-Jing Wang (CoRR, 2014)

Training Excitatory-Inhibitory Recurrent Neural Networks for Cognitive Tasks: A Simple and Flexible Framework. - H. Francis Song; Guangyu R. Yang; Xiao-Jing Wang (PLoS Comput. Biol., 2016)

Machine Theory of Mind. - Neil C. Rabinowitz; Frank Perbet; H. Francis Song; Chiyuan Zhang; S. M. Ali Eslami; Matthew M. Botvinick (ICML, 2018)

Relational inductive biases, deep learning, and graph networks. - Peter W. Battaglia; Jessica B. Hamrick; Victor Bapst; Alvaro Sanchez-Gonzalez; Vinícius Flores Zambaldi; Mateusz Malinowski; Andrea Tacchetti; David Raposo; Adam Santoro; Ryan Faulkner 001; Çaglar Gülçehre; H. Francis Song; et al. (CoRR, 2018)

Relational Forward Models for Multi-Agent Learning. - Andrea Tacchetti; H. Francis Song; Pedro A. M. Mediano; Vinícius Flores Zambaldi; Neil C. Rabinowitz; Thore Graepel; Matthew M. Botvinick; Peter W. Battaglia (CoRR, 2018)

Relational Forward Models for Multi-Agent Learning. - 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 (ICLR (Poster), 2019)

Bayesian Action Decoder for Deep Multi-Agent Reinforcement Learning. - Jakob N. Foerster; H. Francis Song; Edward Hughes 001; Neil Burch; Iain Dunning; Shimon Whiteson; Matthew M. Botvinick; Michael Bowling (ICML, 2019)

V-MPO: On-Policy Maximum a Posteriori Policy Optimization for Discrete and Continuous Control. - H. Francis Song; Abbas Abdolmaleki; Jost Tobias Springenberg; Aidan Clark; Hubert Soyer; Jack W. Rae; Seb Noury; Arun Ahuja; Siqi Liu 002; Dhruva Tirumala; Nicolas Heess; Dan Belov; et al. (ICLR, 2020)

A distributional view on multi-objective policy optimization. - Abbas Abdolmaleki; Sandy H. Huang; Leonard Hasenclever; Michael Neunert; H. Francis Song; Martina Zambelli; Murilo F. Martins; Nicolas Heess; Raia Hadsell; Martin A. Riedmiller (ICML, 2020)

Stabilizing Transformers for Reinforcement Learning. - 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; et al. (ICML, 2020)

The Hanabi challenge: A new frontier for AI research. - Nolan Bard; Jakob N. Foerster; Sarath Chandar; Neil Burch; Marc Lanctot; H. Francis Song; Emilio Parisotto; Vincent Dumoulin; Subhodeep Moitra; Edward Hughes 001; Iain Dunning; Shibl Mourad; et al. (Artif. Intell., 2020)

Alchemy: A benchmark and analysis toolkit for meta-reinforcement learning agents. - Jane Wang 001; 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; et al. (NeurIPS Datasets and Benchmarks, 2021)

Alchemy: A structured task distribution for meta-reinforcement learning. - 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; et al. (CoRR, 2021)

Synthetic Returns for Long-Term Credit Assignment. - David Raposo; Samuel Ritter; Adam Santoro; Greg Wayne; Theophane Weber; Matt M. Botvinick; Hado van Hasselt; H. Francis Song (CoRR, 2021)

Scaling Language Models: Methods, Analysis & Insights from Training Gopher. - 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; et al. (CoRR, 2021)

Red Teaming Language Models with Language Models. - Ethan Perez; Saffron Huang; H. Francis Song; Trevor Cai; Roman Ring; John Aslanides; Amelia Glaese; Nat McAleese; Geoffrey Irving (EMNLP, 2022)

Teaching language models to support answers with verified quotes. - 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 (CoRR, 2022)

Solving math word problems with process- and outcome-based feedback. - Jonathan Uesato; Nate Kushman; Ramana Kumar; H. Francis Song; Noah Y. Siegel; Lisa Wang; Antonia Creswell; Geoffrey Irving; Irina Higgins (CoRR, 2022)

From motor control to team play in simulated humanoid football. - Siqi Liu 002; Guy Lever; Zhe Wang 055; Josh Merel; S. M. Ali Eslami; Daniel Hennes; Wojciech M. Czarnecki; Yuval Tassa; Shayegan Omidshafiei; Abbas Abdolmaleki; Noah Y. Siegel; Leonard Hasenclever; et al. (Sci. Robotics, 2022)

Figure Data for the paper "From Motor Control to Team Play in Simulated Humanoid Football". - Siqi Liu 002; Guy Lever; Zhe Wang 055; Josh Merel; S. M. Ali Eslami; Daniel Hennes; Wojciech Czarnecki 001; Yuval Tassa; Shayegan Omidshafiei; Abbas Abdolmaleki; Noah Y. Siegel; Leonard Hasenclever; et al. (Zenodo, 2022)