Demis Hassabis

发表

Approximate Hubel-Wiesel Modules and the Data Structures of Neural Computation pdf

Joel Z. Leibo, Julien Cornebise, Sergio Gómez, 2015, ArXiv.

Tackling Climate Change with Machine Learning pdf

Yoshua Bengio, Demis Hassabis, David Rolnick, 2019, ACM Comput. Surv..

A general reinforcement learning algorithm that masters chess, shogi, and Go through self-play

Demis Hassabis, Karen Simonyan, David Silver, 2018, Science.

Noisy Networks for Exploration pdf

Shane Legg, Alex Graves, Demis Hassabis, 2017, ICLR.

Learning Dynamic State Abstractions for Model-Based Reinforcement Learning

Demis Hassabis, Karol Gregor, Fabio Viola, 2018 .

Imagination-Augmented Agents for Deep Reinforcement Learning

Razvan Pascanu, Demis Hassabis, David Silver, 2017, NIPS.

Unsupervised deep learning identifies semantic disentanglement in single inferotemporal face patch neurons

Demis Hassabis, Doris Y. Tsao, Matthew Botvinick, 2020, Nature Communications.

Improved protein structure prediction using potentials from deep learning

Demis Hassabis, Karen Simonyan, David T. Jones, 2020, Nature.

Hybrid computing using a neural network with dynamic external memory

Sergio Gomez Colmenarejo, Alex Graves, Demis Hassabis, 2016, Nature.

The Technology of Artificial Intelligence

Demis Hassabis, D. Hassabis, 2016 .

Decoding future state representations during planning

Zeb Kurth-Nelson, Peter Dayan, Demis Hassabis, 2013 .

Turing centenary: Is the brain a good model for machine intelligence?

Demis Hassabis, Amnon Shashua, Rodney Brooks, 2012, Nature.

Psychlab: A Psychology Laboratory for Deep Reinforcement Learning Agents pdf

Shane Legg, Joel Z. Leibo, Demis Hassabis, 2018, ArXiv.

Grounded Language Learning in a Simulated 3D World pdf

Demis Hassabis, Max Jaderberg, Wojciech Czarnecki, 2017, ArXiv.

Mastering Atari, Go, chess and shogi by planning with a learned model

Demis Hassabis, Karen Simonyan, David Silver, 2019, Nature.

Unsupervised Predictive Memory in a Goal-Directed Agent pdf

Joel Z. Leibo, Demis Hassabis, Koray Kavukcuoglu, 2018, ArXiv.

Human-level control through deep reinforcement learning

Shane Legg, Alex Graves, Marc G. Bellemare, 2015, Nature.

SCAN: Learning Abstract Hierarchical Compositional Visual Concepts pdf

Demis Hassabis, Christopher Burgess, Matthew Botvinick, 2017, ArXiv.

Vector-based navigation using grid-like representations in artificial agents

Razvan Pascanu, Raia Hadsell, Fabio Viola, 2018, Nature.

Memory-based Parameter Adaptation pdf

Razvan Pascanu, Demis Hassabis, Oriol Vinyals, 2018, ICLR.

A model of egocentric to allocentric understanding in mammalian brains

Demis Hassabis, Charles Blundell, Benigno Uria, 2020, bioRxiv.

Cortical midline involvement in autobiographical memory

Demis Hassabis, Eleanor A. Maguire, Jennifer J. Summerfield, 2009, NeuroImage.

Parallel WaveNet: Fast High-Fidelity Speech Synthesis

Heiga Zen, Erich Elsen, Alex Graves, 2017, ICML.

Letter to the Editor: Research Priorities for Robust and Beneficial Artificial Intelligence: An Open Letter

Thomas G. Dietterich, Eric Horvitz, Francesca Rossi, 2015, AI Mag..

DeepMind Lab pdf

Shane Legg, Víctor Valdés, Joel Z. Leibo, 2016, ArXiv.

Mastering Chess and Shogi by Self-Play with a General Reinforcement Learning Algorithm pdf

Demis Hassabis, Karen Simonyan, David Silver, 2017, ArXiv.

MEMO: A Deep Network for Flexible Combination of Episodic Memories pdf

Demis Hassabis, Martin J. Chadwick, Charles Blundell, 2020, ICLR.

The Forget-me-not Process

Joel Veness, Michael H. Bowling, Demis Hassabis, 2016, NIPS.

Clinically applicable deep learning for diagnosis and referral in retinal disease

Geraint Rees, Demis Hassabis, Olaf Ronneberger, 2018, Nature Medicine.

Neural Episodic Control

Demis Hassabis, Oriol Vinyals, Daan Wierstra, 2017, ICML.

Protein structure prediction using multiple deep neural networks in the 13th Critical Assessment of Protein Structure Prediction (CASP13)

Pushmeet Kohli, Demis Hassabis, Karen Simonyan, 2019, Proteins.

Model-Free Episodic Control pdf

Joel Z. Leibo, Demis Hassabis, Yazhe Li, 2016, ArXiv.

Overcoming catastrophic forgetting in neural networks

Razvan Pascanu, Raia Hadsell, Joel Veness, 2016, Proceedings of the National Academy of Sciences.

Human-level performance in 3D multiplayer games with population-based reinforcement learning

Guy Lever, Joel Z. Leibo, Demis Hassabis, 2018, Science.

Building Machines that Learn and Think for Themselves: Commentary on Lake et al., Behavioral and Brain Sciences, 2017

Tom Schaul, Nando de Freitas, Shane Legg, 2017, 1711.08378.

Mastering the game of Go without human knowledge

Demis Hassabis, Karen Simonyan, Fan Hui, 2017, Nature.

A distributional code for value in dopamine-based reinforcement learning

Zeb Kurth-Nelson, Clara Kwon Starkweather, Naoshige Uchida, 2020, Nature.

Learning and Querying Fast Generative Models for Reinforcement Learning pdf

Fabio Viola, Demis Hassabis, Daan Wierstra, 2018, ArXiv.

Mastering the game of Go with deep neural networks and tree search

Demis Hassabis, Koray Kavukcuoglu, David Silver, 2016, Nature.

SCAN: Learning Hierarchical Compositional Visual Concepts

Murray Shanahan, Demis Hassabis, Matthew Botvinick, 2017, ICLR.

A model of structure learning, inference, and generation for scene understanding

Peter Dayan, Demis Hassabis, Peter W. Battaglia, 2017, CogSci.

Acquisition of Chess Knowledge in AlphaZero pdf

Demis Hassabis, Ulrich Paquet, Thomas McGrath, 2021, ArXiv.

Alchemy: A structured task distribution for meta-reinforcement learning pdf

Zeb Kurth-Nelson, Demis Hassabis, Matthew Botvinick, 2021, ArXiv.

Scaling Language Models: Methods, Analysis & Insights from Training Gopher pdf

Po-Sen Huang, Erich Elsen, Arthur Mensch, 2021, ArXiv.

Alchemy: A benchmark and analysis toolkit for meta-reinforcement learning agents

Zeb Kurth-Nelson, Demis Hassabis, Matthew Botvinick, 2021, NeurIPS Datasets and Benchmarks.

Developing Deep Learning Continuous Risk Models for Early Adverse Event Prediction in Electronic Health Records: an AKI Case Study

Geraint Rees, Demis Hassabis, Shakir Mohamed, 2019 .

Protein structure prediction using multiple deep neural networks in the 13th Critical Assessment of Protein Structure Prediction (CASP13)

Pushmeet Kohli, Demis Hassabis, Karen Simonyan, 2019, Proteins.

Role of the hippocampus in imagination and future thinking

Demis Hassabis, Eleanor A Maguire, D. Hassabis, 2011, Proceedings of the National Academy of Sciences.

Imagine all the people: how the brain creates and uses personality models to predict behavior.

Demis Hassabis, Raymond A Mar, R Nathan Spreng, 2014, Cerebral cortex.

Unveiling the predictive power of static structure in glassy systems

Pushmeet Kohli, Samuel S. Schoenholz, Demis Hassabis, 2020 .

Imagining fictitious and future experiences: Evidence from developmental amnesia

Demis Hassabis, Eleanor A. Maguire, Faraneh Vargha-Khadem, 2010, Neuropsychologia.

Differential engagement of brain regions within a ‘core’ network during scene construction

Demis Hassabis, Eleanor A. Maguire, Jennifer J. Summerfield, 2010, Neuropsychologia.

Semantic representations in the temporal pole predict false memories

Demis Hassabis, Dharshan Kumaran, Hugo J Spiers, 2016, Proceedings of the National Academy of Sciences.

Impaired spatial and non-spatial configural learning in patients with hippocampal pathology

Demis Hassabis, Eleanor A. Maguire, Hugo J. Spiers, 2007, Neuropsychologia.

Decoding Representations of Scenes in the Medial Temporal Lobes

Nikolaus Weiskopf, Demis Hassabis, Dharshan Kumaran, 2011, Hippocampus.

Detecting Representations of Recent and Remote Autobiographical Memories in vmPFC and Hippocampus

Nikolaus Weiskopf, Antoine Lutti, Demis Hassabis, 2012, The Journal of Neuroscience.

Decoding overlapping memories in the medial temporal lobes using high-resolution fMRI

Demis Hassabis, Eleanor A Maguire, D. Hassabis, 2011, Learning & memory.

Artificial Intelligence: Chess match of the century

Demis Hassabis, D. Hassabis, 2017, Nature.