Devlin, Sam

16 publications

ICLRW 2025 Adapting a World Model for Trajectory Following in a 3D Game Marko Tot, Shu Ishida, Abdelhak Lemkhenter, David Bignell, Pallavi Choudhury, Chris Lovett, Luis França, Matheus Ribeiro Furtado de Mendonça, Tarun Gupta, Darren Gehring, Sam Devlin, Sergio Valcarcel Macua, Raluca Georgescu

ICML 2025 Scaling Laws for Pre-Training Agents and World Models Tim Pearce, Tabish Rashid, David Bignell, Raluca Georgescu, Sam Devlin, Katja Hofmann

ICLRW 2025 Scaling Laws for Pre-Training Agents and World Models Tim Pearce, Tabish Rashid, David Bignell, Raluca Georgescu, Sam Devlin, Katja Hofmann

ICMLW 2024 Efficient Offline Reinforcement Learning: The Critic Is Critical Adam Jelley, Trevor McInroe, Sam Devlin, Amos Storkey

ICLR 2023 Contrastive Meta-Learning for Partially Observable Few-Shot Learning Adam Jelley, Amos Storkey, Antreas Antoniou, Sam Devlin

ICLR 2023 Imitating Human Behaviour with Diffusion Models Tim Pearce, Tabish Rashid, Anssi Kanervisto, Dave Bignell, Mingfei Sun, Raluca Georgescu, Sergio Valcarcel Macua, Shan Zheng Tan, Ida Momennejad, Katja Hofmann, Sam Devlin

AAAI 2022 Deterministic and Discriminative Imitation (d2-Imitation): Revisiting Adversarial Imitation for Sample Efficiency Mingfei Sun, Sam Devlin, Katja Hofmann, Shimon Whiteson

NeurIPSW 2022 Imitating Human Behaviour with Diffusion Models Tim Pearce, Tabish Rashid, Anssi Kanervisto, David Bignell, Mingfei Sun, Raluca Georgescu, Sergio Valcarcel Macua, Shan Zheng Tan, Ida Momennejad, Katja Hofmann, Sam Devlin

ICLRW 2022 Towards Flexible Inference in Sequential Decision Problems via Bidirectional Transformers Micah Carroll, Jessy Lin, Orr Paradise, Raluca Georgescu, Mingfei Sun, David Bignell, Stephanie Milani, Katja Hofmann, Matthew Hausknecht, Anca Dragan, Sam Devlin

NeurIPS 2022 Uni[MASK]: Unified Inference in Sequential Decision Problems Micah Carroll, Orr Paradise, Jessy Lin, Raluca Georgescu, Mingfei Sun, David Bignell, Stephanie Milani, Katja Hofmann, Matthew Hausknecht, Anca Dragan, Sam Devlin

AISTATS 2021 Meta-Learning Divergences for Variational Inference Ruqi Zhang, Yingzhen Li, Christopher De Sa, Sam Devlin, Cheng Zhang

ICML 2021 Navigation Turing Test (NTT): Learning to Evaluate Human-like Navigation Sam Devlin, Raluca Georgescu, Ida Momennejad, Jaroslaw Rzepecki, Evelyn Zuniga, Gavin Costello, Guy Leroy, Ali Shaw, Katja Hofmann

UAI 2021 Strategically Efficient Exploration in Competitive Multi-Agent Reinforcement Learning Robert Loftin, Aadirupa Saha, Sam Devlin, Katja Hofmann

ICLR 2020 AMRL: Aggregated Memory for Reinforcement Learning Jacob Beck, Kamil Ciosek, Sam Devlin, Sebastian Tschiatschek, Cheng Zhang, Katja Hofmann

NeurIPS 2019 Generalization in Reinforcement Learning with Selective Noise Injection and Information Bottleneck Maximilian Igl, Kamil Ciosek, Yingzhen Li, Sebastian Tschiatschek, Cheng Zhang, Sam Devlin, Katja Hofmann

AAAI 2015 Expressing Arbitrary Reward Functions as Potential-Based Advice Anna Harutyunyan, Sam Devlin, Peter Vrancx, Ann Nowé