Neural Photo Editing with Introspective Adversarial Networks. - Andrew Brock; Theodore Lim; James M. Ritchie; Nick Weston (ICLR (Poster), 2017)

FreezeOut: Accelerate Training by Progressively Freezing Layers. - Andrew Brock; Theodore Lim; James M. Ritchie; Nick Weston (CoRR, 2017)

SMASH: One-Shot Model Architecture Search through HyperNetworks. - Andrew Brock; Theodore Lim; James M. Ritchie; Nick Weston (ICLR (Poster), 2018)

Large Scale GAN Training for High Fidelity Natural Image Synthesis. - Andrew Brock; Jeff Donahue; Karen Simonyan (ICLR, 2019)

TF-Replicator: Distributed Machine Learning for Researchers. - Peter Buchlovsky; David Budden; Dominik Grewe; Chris Jones; John Aslanides; Frederic Besse; Andy Brock; Aidan Clark; Sergio Gomez Colmenarejo; Aedan Pope; Fabio Viola; Dan Belov (CoRR, 2019)

Evolving Normalization-Activation Layers. - Hanxiao Liu; Andy Brock; Karen Simonyan; Quoc Le 001 (NeurIPS, 2020)

Training Generative Adversarial Networks by Solving Ordinary Differential Equations. - Chongli Qin; Yan Wu 010; Jost Tobias Springenberg; Andy Brock; Jeff Donahue; Timothy P. Lillicrap; Pushmeet Kohli (NeurIPS, 2020)

BYOL works even without batch statistics. - Pierre H. Richemond; Jean-Bastien Grill; Florent Altché; Corentin Tallec; Florian Strub; Andrew Brock; Samuel L. Smith; Soham De; Razvan Pascanu; Bilal Piot; Michal Valko (CoRR, 2020)

Characterizing signal propagation to close the performance gap in unnormalized ResNets. - Andrew Brock; Soham De; Samuel L. Smith (ICLR, 2021)

High-Performance Large-Scale Image Recognition Without Normalization. - Andy Brock; Soham De; Samuel L. Smith; Karen Simonyan (ICML, 2021)

Perceiver: General Perception with Iterative Attention. - Andrew Jaegle; Felix Gimeno; Andy Brock; Oriol Vinyals; Andrew Zisserman; João Carreira 001 (ICML, 2021)

Skillful Precipitation Nowcasting using Deep Generative Models of Radar. - Suman V. Ravuri; Karel Lenc; Matthew Willson; Dmitry Kangin; Rémi Lam; Piotr Mirowski; Megan Fitzsimons; Maria Athanassiadou; Sheleem Kashem; Sam Madge; Rachel Prudden; Amol Mandhane; et al. (CoRR, 2021)

Drawing Multiple Augmentation Samples Per Image During Training Efficiently Decreases Test Error. - Stanislav Fort; Andrew Brock; Razvan Pascanu; Soham De; Samuel L. Smith (CoRR, 2021)

Skilful precipitation nowcasting using deep generative models of radar. - Suman V. Ravuri; Karel Lenc; Matthew Willson; Dmitry Kangin; Rémi Lam; Piotr Mirowski; Megan Fitzsimons; Maria Athanassiadou; Sheleem Kashem; Sam Madge; Rachel Prudden; Amol Mandhane; et al. (Nat., 2021)

Towards Learning Universal Audio Representations. - Luyu Wang; Pauline Luc; Yan Wu 010; Adrià Recasens; Lucas Smaira; Andrew Brock; Andrew Jaegle; Jean-Baptiste Alayrac; Sander Dieleman; João Carreira 001; Aäron van den Oord (ICASSP, 2022)

Perceiver IO: A General Architecture for Structured Inputs & Outputs. - Andrew Jaegle; Sebastian Borgeaud; Jean-Baptiste Alayrac; Carl Doersch; Catalin Ionescu; David Ding; Skanda Koppula; Daniel Zoran; Andrew Brock; Evan Shelhamer; Olivier J. Hénaff; Matthew M. Botvinick; et al. (ICLR, 2022)

Improving Language Models by Retrieving from Trillions of Tokens. - Sebastian Borgeaud; Arthur Mensch; Jordan Hoffmann; Trevor Cai; Eliza Rutherford; Katie Millican; George van den Driessche 002; Jean-Baptiste Lespiau; Bogdan Damoc; Aidan Clark; Diego de Las Casas; Aurelia Guy; et al. (ICML, 2022)

Flamingo: a Visual Language Model for Few-Shot Learning. - Jean-Baptiste Alayrac; Jeff Donahue; Pauline Luc; Antoine Miech; Iain Barr; Yana Hasson; Karel Lenc; Arthur Mensch; Katherine Millican; Malcolm Reynolds; Roman Ring; Eliza Rutherford; et al. (NeurIPS, 2022)

Flamingo: a Visual Language Model for Few-Shot Learning. - Jean-Baptiste Alayrac; Jeff Donahue; Pauline Luc; Antoine Miech; Iain Barr; Yana Hasson; Karel Lenc; Arthur Mensch; Katie Millican; Malcolm Reynolds; Roman Ring; Eliza Rutherford; et al. (CoRR, 2022)

Deep Transformers without Shortcuts: Modifying Self-attention for Faithful Signal Propagation. - Bobby He; James Martens; Guodong Zhang; Aleksandar Botev; Andrew Brock; Samuel L. Smith; Yee Whye Teh (ICLR, 2023)

Spatial Functa: Scaling Functa to ImageNet Classification and Generation. - Matthias Bauer 001; Emilien Dupont; Andy Brock; Dan Rosenbaum; Jonathan Schwarz; Hyunjik Kim (CoRR, 2023)

ConvNets Match Vision Transformers at Scale. - Samuel L. Smith; Andrew Brock; Leonard Berrada; Soham De (CoRR, 2023)

RecurrentGemma: Moving Past Transformers for Efficient Open Language Models. - Aleksandar Botev; Soham De; Samuel L. Smith; Anushan Fernando; George-Cristian Muraru; Ruba Haroun; Leonard Berrada; Razvan Pascanu; Pier Giuseppe Sessa; Robert Dadashi; Léonard Hussenot; Johan Ferret; et al. (CoRR, 2024)

Gemma 2: Improving Open Language Models at a Practical Size. - Morgane Rivière; Shreya Pathak; Pier Giuseppe Sessa; Cassidy Hardin; Surya Bhupatiraju; Léonard Hussenot; Thomas Mesnard; Bobak Shahriari; Alexandre Ramé; Johan Ferret; Peter Liu; Pouya Tafti; et al. (CoRR, 2024)