The Deterministic Information Bottleneck. - DJ Strouse; David J. Schwab (UAI, 2016)

Learning to Share and Hide Intentions using Information Regularization. - Daniel Strouse; Max Kleiman-Weiner; Josh Tenenbaum 001; Matthew M. Botvinick; David J. Schwab (NeurIPS, 2018)

Intrinsic Social Motivation via Causal Influence in Multi-Agent RL. - Natasha Jaques; Angeliki Lazaridou; Edward Hughes 001; Çaglar Gülçehre; Pedro A. Ortega; DJ Strouse; Joel Z. Leibo; Nando de Freitas (CoRR, 2018)

InfoBot: Transfer and Exploration via the Information Bottleneck. - Anirudh Goyal; Riashat Islam; Daniel Strouse; Zafarali Ahmed; Hugo Larochelle; Matthew M. Botvinick; Yoshua Bengio; Sergey Levine (ICLR (Poster), 2019)

Social Influence as Intrinsic Motivation for Multi-Agent Deep Reinforcement Learning. - Natasha Jaques; Angeliki Lazaridou; Edward Hughes 001; Çaglar Gülçehre; Pedro A. Ortega; DJ Strouse; Joel Z. Leibo; Nando de Freitas (ICML, 2019)

A Neural Architecture for Designing Truthful and Efficient Auctions. - Andrea Tacchetti; DJ Strouse; Marta Garnelo; Thore Graepel; Yoram Bachrach (CoRR, 2019)

The Information Bottleneck and Geometric Clustering. - DJ Strouse; David J. Schwab (Neural Comput., 2019)

How Dendrites Affect Online Recognition Memory. - Xundong Wu; Gabriel C. Mel; DJ Strouse; Bartlett W. Mel (PLoS Comput. Biol., 2019)

Collaborating with Humans without Human Data. - DJ Strouse; Kevin R. McKee; Matt M. Botvinick; Edward Hughes 001; Richard Everett 001 (NeurIPS, 2021)

Learning more skills through optimistic exploration. - DJ Strouse; Kate Baumli; David Warde-Farley; Volodymyr Mnih; Steven Stenberg Hansen (ICLR, 2022)

Semantic Exploration from Language Abstractions and Pretrained Representations. - Allison C. Tam; Neil C. Rabinowitz; Andrew K. Lampinen; Nicholas A. Roy; Stephanie C. Y. Chan; DJ Strouse; Jane Wang 001; Andrea Banino; Felix Hill (NeurIPS, 2022)

Melting Pot 2.0. - John P. Agapiou; Alexander Sasha Vezhnevets; Edgar A. Duéñez-Guzmán; Jayd Matyas; Yiran Mao; Peter Sunehag; Raphael Köster; Udari Madhushani; Kavya Kopparapu; Ramona Comanescu; DJ Strouse; Michael Bradley Johanson; et al. (CoRR, 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; et al. (ICLR, 2023)

Confronting Reward Model Overoptimization with Constrained RLHF. - Ted Moskovitz; Aaditya K. Singh; DJ Strouse; Tuomas Sandholm; Ruslan Salakhutdinov; Anca D. Dragan; Stephen Marcus McAleer (ICLR, 2024)

Tokenization counts: the impact of tokenization on arithmetic in frontier LLMs. - Aaditya K. Singh; DJ Strouse (CoRR, 2024)

HARP: A challenging human-annotated math reasoning benchmark. - Albert S. Yue; Lovish Madaan; Ted Moskovitz; DJ Strouse; Aaditya K. Singh (CoRR, 2024)