Cortical midline involvement in autobiographical memory. - Jennifer J. Summerfield; Demis Hassabis; Eleanor A. Maguire (NeuroImage, 2009)

Letter to the Editor: Research Priorities for Robust and Beneficial Artificial Intelligence: An Open Letter. - Stuart Russell 001; Tom Dietterich; Eric Horvitz; Bart Selman; Francesca Rossi 001; Demis Hassabis; Shane Legg; Mustafa Suleyman; Dileep George; D. Scott Phoenix (AI Mag., 2015)

Approximate Hubel-Wiesel Modules and the Data Structures of Neural Computation. - Joel Z. Leibo; Julien Cornebise; Sergio Gómez; Demis Hassabis (CoRR, 2015)

Human-level control through deep reinforcement learning. - Volodymyr Mnih; Koray Kavukcuoglu; David Silver; Andrei A. Rusu; Joel Veness; Marc G. Bellemare; Alex Graves; Martin A. Riedmiller; Andreas Fidjeland; Georg Ostrovski; Stig Petersen; Charles Beattie; et al. (Nat., 2015)

The Forget-me-not Process. - Kieran Milan; Joel Veness; James Kirkpatrick; Michael H. Bowling; Anna Koop; Demis Hassabis (NIPS, 2016)

DeepMind Lab. - Charles Beattie; Joel Z. Leibo; Denis Teplyashin; Tom Ward; Marcus Wainwright; Heinrich Küttler; Andrew Lefrancq; Simon Green; Víctor Valdés; Amir Sadik; Julian Schrittwieser; Keith Anderson; et al. (CoRR, 2016)

Model-Free Episodic Control. - Charles Blundell; Benigno Uria; Alexander Pritzel; Yazhe Li; Avraham Ruderman; Joel Z. Leibo; Jack W. Rae; Daan Wierstra; Demis Hassabis (CoRR, 2016)

Overcoming catastrophic forgetting in neural networks. - James Kirkpatrick; Razvan Pascanu; Neil C. Rabinowitz; Joel Veness; Guillaume Desjardins; Andrei A. Rusu; Kieran Milan; John Quan; Tiago Ramalho; Agnieszka Grabska-Barwinska; Demis Hassabis; Claudia Clopath; et al. (CoRR, 2016)

Hybrid computing using a neural network with dynamic external memory. - Alex Graves; Greg Wayne; Malcolm Reynolds; Tim Harley; Ivo Danihelka; Agnieszka Grabska-Barwinska; Sergio Gomez Colmenarejo; Edward Grefenstette; Tiago Ramalho; John P. Agapiou; Adrià Puigdomènech Badia; Karl Moritz Hermann; et al. (Nat., 2016)

Mastering the game of Go with deep neural networks and tree search. - David Silver; Aja Huang; Chris J. Maddison; Arthur Guez; Laurent Sifre; George van den Driessche 002; Julian Schrittwieser; Ioannis Antonoglou; Vedavyas Panneershelvam; Marc Lanctot; Sander Dieleman; Dominik Grewe; et al. (Nat., 2016)

A model of structure learning, inference, and generation for scene understanding. - David Raposo; Peter Dayan; Demis Hassabis; Peter W. Battaglia (CogSci, 2017)

Neural Episodic Control. - Alexander Pritzel; Benigno Uria; Sriram Srinivasan 005; Adrià Puigdomènech Badia; Oriol Vinyals; Demis Hassabis; Daan Wierstra; Charles Blundell (ICML, 2017)

Imagination-Augmented Agents for Deep Reinforcement Learning. - Sébastien Racanière; Theophane Weber; David P. Reichert; Lars Buesing; Arthur Guez; Danilo Jimenez Rezende; Adrià Puigdomènech Badia; Oriol Vinyals; Nicolas Heess; Yujia Li 001; Razvan Pascanu; Peter W. Battaglia; et al. (NIPS, 2017)

Noisy Networks for Exploration. - Meire Fortunato; Mohammad Gheshlaghi Azar; Bilal Piot; Jacob Menick; Ian Osband; Alex Graves; Vlad Mnih; Rémi Munos; Demis Hassabis; Olivier Pietquin; Charles Blundell; Shane Legg (CoRR, 2017)

Grounded Language Learning in a Simulated 3D World. - Karl Moritz Hermann; Felix Hill; Simon Green; Fumin Wang; Ryan Faulkner 001; Hubert Soyer; David Szepesvari; Wojciech Marian Czarnecki; Max Jaderberg; Denis Teplyashin; Marcus Wainwright; Chris Apps; et al. (CoRR, 2017)

SCAN: Learning Abstract Hierarchical Compositional Visual Concepts. - Irina Higgins; Nicolas Sonnerat; Loïc Matthey; Arka Pal; Christopher P. Burgess; Matthew M. Botvinick; Demis Hassabis; Alexander Lerchner (CoRR, 2017)

Building Machines that Learn and Think for Themselves: Commentary on Lake et al., Behavioral and Brain Sciences, 2017. - Matthew M. Botvinick; David G. T. Barrett; Peter W. Battaglia; Nando de Freitas; Dharshan Kumaran; Joel Z. Leibo; Tim Lillicrap; Joseph Modayil; S. Mohamed; Neil C. Rabinowitz; Danilo Jimenez Rezende; Adam Santoro; et al. (CoRR, 2017)

Mastering Chess and Shogi by Self-Play with a General Reinforcement Learning Algorithm. - David Silver; Thomas Hubert; Julian Schrittwieser; Ioannis Antonoglou; Matthew Lai; Arthur Guez; Marc Lanctot; Laurent Sifre; Dharshan Kumaran; Thore Graepel; Timothy P. Lillicrap; Karen Simonyan; et al. (CoRR, 2017)

Mastering the game of Go without human knowledge. - David Silver; Julian Schrittwieser; Karen Simonyan; Ioannis Antonoglou; Aja Huang; Arthur Guez; Thomas Hubert; Lucas Baker; Matthew Lai; Adrian Bolton; Yutian Chen 001; Timothy P. Lillicrap; et al. (Nat., 2017)

Noisy Networks For Exploration. - Meire Fortunato; Mohammad Gheshlaghi Azar; Bilal Piot; Jacob Menick; Matteo Hessel; Ian Osband; Alex Graves; Volodymyr Mnih; Rémi Munos; Demis Hassabis; Olivier Pietquin; Charles Blundell; et al. (ICLR (Poster), 2018)

SCAN: Learning Hierarchical Compositional Visual Concepts. - Irina Higgins; Nicolas Sonnerat; Loic Matthey; Arka Pal; Christopher P. Burgess; Matko Bosnjak; Murray Shanahan; Matthew M. Botvinick; Demis Hassabis; Alexander Lerchner (ICLR (Poster), 2018)

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)

Parallel WaveNet: Fast High-Fidelity Speech Synthesis. - Aäron van den Oord; Yazhe Li; Igor Babuschkin; Karen Simonyan; Oriol Vinyals; Koray Kavukcuoglu; George van den Driessche 002; Edward Lockhart; Luis C. Cobo; Florian Stimberg; Norman Casagrande; Dominik Grewe; et al. (ICML, 2018)

Psychlab: A Psychology Laboratory for Deep Reinforcement Learning Agents. - Joel Z. Leibo; Cyprien de Masson d'Autume; Daniel Zoran; David Amos; Charles Beattie; Keith Anderson; Antonio García Castañeda; Manuel Sanchez; Simon Green; Audrunas Gruslys; Shane Legg; Demis Hassabis; et al. (CoRR, 2018)

Learning and Querying Fast Generative Models for Reinforcement Learning. - Lars Buesing; Theophane Weber; Sébastien Racanière; S. M. Ali Eslami; Danilo Jimenez Rezende; David P. Reichert; Fabio Viola; Frederic Besse; Karol Gregor; Demis Hassabis; Daan Wierstra (CoRR, 2018)

Unsupervised Predictive Memory in a Goal-Directed Agent. - Greg Wayne; Chia-Chun Hung; David Amos; Mehdi Mirza; Arun Ahuja; Agnieszka Grabska-Barwinska; Jack W. Rae; Piotr Mirowski; Joel Z. Leibo; Adam Santoro; Mevlana Gemici; Malcolm Reynolds; et al. (CoRR, 2018)

Human-level performance in first-person multiplayer games with population-based deep reinforcement learning. - Max Jaderberg; Wojciech M. Czarnecki; Iain Dunning; Luke Marris; Guy Lever; Antonio García Castañeda; Charles Beattie; Neil C. Rabinowitz; Ari S. Morcos; Avraham Ruderman; Nicolas Sonnerat; Tim Green; et al. (CoRR, 2018)

Vector-based navigation using grid-like representations in artificial agents. - Andrea Banino; Caswell Barry; Benigno Uria; Charles Blundell; Timothy P. Lillicrap; Piotr Mirowski; Alexander Pritzel; Martin J. Chadwick; Thomas Degris; Joseph Modayil; Greg Wayne; Hubert Soyer; et al. (Nat., 2018)

Grandmaster level in StarCraft II using multi-agent reinforcement learning. - Oriol Vinyals; Igor Babuschkin; Wojciech M. Czarnecki; Michaël Mathieu; Andrew Dudzik; Junyoung Chung; David H. Choi; Richard Powell; Timo Ewalds; Petko Georgiev; Junhyuk Oh; Dan Horgan; et al. (Nat., 2019)

MEMO: A Deep Network for Flexible Combination of Episodic Memories. - Andrea Banino; Adrià Puigdomènech Badia; Raphael Köster; Martin J. Chadwick; Vinícius Flores Zambaldi; Demis Hassabis; Caswell Barry; Matthew M. Botvinick; Dharshan Kumaran; Charles Blundell (ICLR, 2020)

Assessing Game Balance with AlphaZero: Exploring Alternative Rule Sets in Chess. - Nenad Tomasev; Ulrich Paquet; Demis Hassabis; Vladimir Kramnik (CoRR, 2020)

A distributional code for value in dopamine-based reinforcement learning. - Will Dabney; Zeb Kurth-Nelson; Naoshige Uchida; Clara Kwon Starkweather; Demis Hassabis; Rémi Munos; Matthew M. Botvinick (Nat., 2020)

Mastering Atari, Go, chess and shogi by planning with a learned model. - Julian Schrittwieser; Ioannis Antonoglou; Thomas Hubert; Karen Simonyan; Laurent Sifre; Simon Schmitt; Arthur Guez; Edward Lockhart; Demis Hassabis; Thore Graepel; Timothy P. Lillicrap; David Silver (Nat., 2020)

Improved protein structure prediction using potentials from deep learning. - Andrew W. Senior; Richard Evans 001; John Jumper; James Kirkpatrick; Laurent Sifre; Tim Green; Chongli Qin; Augustin Zídek; Alexander W. R. Nelson; Alex Bridgland; Hugo Penedones; Stig Petersen; et al. (Nat., 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)

Acquisition of Chess Knowledge in AlphaZero. - Thomas McGrath; Andrei Kapishnikov; Nenad Tomasev; Adam Pearce; Demis Hassabis; Been Kim; Ulrich Paquet; Vladimir Kramnik (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)

Game Plan: What AI can do for Football, and What Football can do for AI. - Karl Tuyls; Shayegan Omidshafiei; Paul Muller; Zhe Wang 055; Jerome T. Connor; Daniel Hennes; Ian Graham; William Spearman; Tim Waskett; Dafydd Steele; Pauline Luc; Adrià Recasens; et al. (J. Artif. Intell. Res., 2021)

Advancing mathematics by guiding human intuition with AI. - Alex Davies; Petar Velickovic; Lars Buesing; Sam Blackwell; Daniel Zheng; Nenad Tomasev; Richard Tanburn; Peter W. Battaglia; Charles Blundell; András Juhász; Marc Lackenby; Geordie Williamson; et al. (Nat., 2021)

Reimagining chess with AlphaZero. - Nenad Tomasev; Ulrich Paquet; Demis Hassabis; Vladimir Kramnik (Commun. ACM, 2022)

Mastering the Game of Stratego with Model-Free Multiagent Reinforcement Learning. - Julien Pérolat; Bart De Vylder; Daniel Hennes; Eugene Tarassov; Florian Strub; Vincent de Boer; Paul Muller; Jerome T. Connor; Neil Burch; Thomas W. Anthony 001; Stephen McAleer; Romuald Elie; et al. (CoRR, 2022)

Improving alignment of dialogue agents via targeted human judgements. - Amelia Glaese; Nat McAleese; Maja Trebacz; John Aslanides; Vlad Firoiu; Timo Ewalds; Maribeth Rauh; Laura Weidinger; Martin J. Chadwick; Phoebe Thacker; Lucy Campbell-Gillingham; Jonathan Uesato; et al. (CoRR, 2022)

AlphaFold Protein Structure Database: massively expanding the structural coverage of protein-sequence space with high-accuracy models. - Mihaly Varadi; Stephen Anyango; Mandar S. Deshpande; Sreenath Nair; Cindy Natassia; Galabina Yordanova; David Yuan; Oana Stroe; Gemma Wood; Agata Laydon; Augustin Zídek; Tim Green; et al. (Nucleic Acids Res., 2022)

Magnetic control of tokamak plasmas through deep reinforcement learning. - Jonas Degrave; Federico Felici; Jonas Buchli; Michael Neunert; Brendan D. Tracey; Francesco Carpanese; Timo Ewalds; Roland Hafner; Abbas Abdolmaleki; Diego de Las Casas; Craig Donner; Leslie Fritz; et al. (Nat., 2022)

Discovering faster matrix multiplication algorithms with reinforcement learning. - Alhussein Fawzi; Matej Balog; Aja Huang; Thomas Hubert; Bernardino Romera-Paredes; Mohammadamin Barekatain; Alexander Novikov 001; Francisco J. R. Ruiz; Julian Schrittwieser; Grzegorz Swirszcz; David Silver; Demis Hassabis; et al. (Nat., 2022)

Figure Data for the paper "Mastering the Game of Stratego with Model-Free Multiagent Reinforcement Learning". - Julien Pérolat; Bart De Vylder; Daniel Hennes; Eugene Tarassov; Florian Strub; Vincent de Boer; Paul Muller; Jerome T. Connor; Neil Burch; Thomas Anthony 001; Stephen McAleer; Romuald Elie; et al. (Zenodo, 2022)

Diversifying AI: Towards Creative Chess with AlphaZero. - Tom Zahavy; Vivek Veeriah; Shaobo Hou; Kevin Waugh; Matthew Lai; Edouard Leurent; Nenad Tomasev; Lisa Schut; Demis Hassabis; Satinder Singh 001 (CoRR, 2023)

Learning to Decode the Surface Code with a Recurrent, Transformer-Based Neural Network. - Johannes Bausch; Andrew W. Senior; Francisco J. H. Heras; Thomas Edlich; Alex Davies; Michael Newman; Cody Jones; Kevin J. Satzinger; Murphy Yuezhen Niu; Sam Blackwell; George Holland; Dvir Kafri; et al. (CoRR, 2023)

TacticAI: an AI assistant for football tactics. - Zhe Wang 055; Petar Velickovic; Daniel Hennes; Nenad Tomasev; Laurel Prince; Michael Kaisers; Yoram Bachrach; Romuald Elie; Li Kevin Wenliang; Federico Piccinini; William Spearman; Ian Graham; et al. (CoRR, 2023)

Bridging the Human-AI Knowledge Gap: Concept Discovery and Transfer in AlphaZero. - Lisa Schut; Nenad Tomasev; Tom McGrath; Demis Hassabis; Ulrich Paquet; Been Kim (CoRR, 2023)

Tackling Climate Change with Machine Learning. - David Rolnick; Priya L. Donti; Lynn H. Kaack; Kelly Kochanski; Alexandre Lacoste; Kris Sankaran; Andrew Slavin Ross; Nikola Milojevic-Dupont; Natasha Jaques; Anna Waldman-Brown; Alexandra Sasha Luccioni; Tegan Maharaj; et al. (ACM Comput. Surv., 2023)

Faster sorting algorithms discovered using deep reinforcement learning. - Daniel J. Mankowitz; Andrea Michi; Anton Zhernov; Marco Gelmi; Marco Selvi; Cosmin Paduraru; Edouard Leurent; Shariq Iqbal; Jean-Baptiste Lespiau; Alex Ahern; Thomas Köppe; Kevin Millikin; et al. (Nat., 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)

Capabilities of Gemini Models in Medicine. - Khaled Saab 003; Tao Tu 001; Wei-Hung Weng; Ryutaro Tanno; David Stutz; Ellery Wulczyn; Fan Zhang; Tim Strother; Chunjong Park; Elahe Vedadi; Juanma Zambrano Chaves; Szu-Yeu Hu; et al. (CoRR, 2024)

Scalable watermarking for identifying large language model outputs. - Sumanth Dathathri; Abigail See; Sumedh Ghaisas; Po-Sen Huang; Rob McAdam; Johannes Welbl; Vandana Bachani; Alex Kaskasoli; Robert Stanforth; Tatiana Matejovicova; Jamie Hayes; Nidhi Vyas; et al. (Nat., 2024)

Learning high-accuracy error decoding for quantum processors. - Johannes Bausch; Andrew W. Senior; Francisco J. H. Heras; Thomas Edlich; Alex Davies; Michael Newman; Cody Jones; Kevin J. Satzinger; Murphy Yuezhen Niu; Sam Blackwell; George Holland; Dvir Kafri; et al. (Nat., 2024)

Gemma 3 Technical Report. - Aishwarya Kamath; Johan Ferret; Shreya Pathak; Nino Vieillard; Ramona Merhej; Sarah Perrin; Tatiana Matejovicova; Alexandre Ramé; Morgane Rivière; Louis Rouillard; Thomas Mesnard; Geoffrey Cideron; et al. (CoRR, 2025)