Memory-based Parameter Adaptation. - Pablo Sprechmann; Siddhant M. Jayakumar; Jack W. Rae; Alexander Pritzel; Adrià Puigdomènech Badia; Benigno Uria; Oriol Vinyals; Demis Hassabis; Razvan Pascanu; Charles Blundell (ICLR (Poster), 2018)

Mix & Match Agent Curricula for Reinforcement Learning. - Wojciech Marian Czarnecki; Siddhant M. Jayakumar; Max Jaderberg; Leonard Hasenclever; Yee Whye Teh; Nicolas Heess; Simon Osindero; Razvan Pascanu (ICML, 2018)

Been There, Done That: Meta-Learning with Episodic Recall. - Samuel Ritter; Jane X. Wang; Zeb Kurth-Nelson; Siddhant M. Jayakumar; Charles Blundell; Razvan Pascanu; Matthew M. Botvinick (ICML, 2018)

Low-pass Recurrent Neural Networks - A memory architecture for longer-term correlation discovery. - Thomas S. Stepleton; Razvan Pascanu; Will Dabney; Siddhant M. Jayakumar; Hubert Soyer; Rémi Munos (CoRR, 2018)

Adapting Auxiliary Losses Using Gradient Similarity. - Yunshu Du; Wojciech M. Czarnecki; Siddhant M. Jayakumar; Razvan Pascanu; Balaji Lakshminarayanan (CoRR, 2018)

Distilling Policy Distillation. - Wojciech M. Czarnecki; Razvan Pascanu; Simon Osindero; Siddhant M. Jayakumar; Grzegorz Swirszcz; Max Jaderberg (AISTATS, 2019)

Information asymmetry in KL-regularized RL. - Alexandre Galashov; Siddhant M. Jayakumar; Leonard Hasenclever; Dhruva Tirumala; Jonathan Schwarz; Guillaume Desjardins; Wojciech M. Czarnecki; Yee Whye Teh; Razvan Pascanu; Nicolas Heess (ICLR (Poster), 2019)

Meta-learning of Sequential Strategies. - Pedro A. Ortega; Jane X. Wang; Mark Rowland 001; Tim Genewein; Zeb Kurth-Nelson; Razvan Pascanu; Nicolas Heess; Joel Veness; Alexander Pritzel; Pablo Sprechmann; Siddhant M. Jayakumar; Tom McGrath; et al. (CoRR, 2019)

Compressive Transformers for Long-Range Sequence Modelling. - Jack W. Rae; Anna Potapenko; Siddhant M. Jayakumar; Timothy P. Lillicrap (CoRR, 2019)

Multiplicative Interactions and Where to Find Them. - Siddhant M. Jayakumar; Wojciech M. Czarnecki; Jacob Menick; Jonathan Schwarz; Jack W. Rae; Simon Osindero; Yee Whye Teh; Tim Harley; Razvan Pascanu (ICLR, 2020)

Compressive Transformers for Long-Range Sequence Modelling. - Jack W. Rae; Anna Potapenko; Siddhant M. Jayakumar; Chloe Hillier; Timothy P. Lillicrap (ICLR, 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)

Top-KAST: Top-K Always Sparse Training. - Siddhant M. Jayakumar; Razvan Pascanu; Jack W. Rae; Simon Osindero; Erich Elsen (NeurIPS, 2020)

Perception-Prediction-Reaction Agents for Deep Reinforcement Learning. - Adam Stooke; Valentin Dalibard; Siddhant M. Jayakumar; Wojciech M. Czarnecki; Max Jaderberg (CoRR, 2020)

Powerpropagation: A sparsity inducing weight reparameterisation. - Jonathan Schwarz; Siddhant M. Jayakumar; Razvan Pascanu; Peter E. Latham; Yee Whye Teh (NeurIPS, 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)