Bayesian Rose Trees. - Charles Blundell; Yee Whye Teh; Katherine A. Heller (UAI, 2010)

Modelling Genetic Variations using Fragmentation-Coagulation Processes. - Yee Whye Teh; Charles Blundell; Lloyd T. Elliott (NIPS, 2011)

Mixed Cumulative Distribution Networks. - Ricardo Bezerra de Andrade e Silva; Charles Blundell; Yee Whye Teh (AISTATS, 2011)

Look-Ahead Monte Carlo with People. - Charles Blundell; Adam Sanborn; Thomas L. Griffiths 001 (CogSci, 2012)

Modelling Reciprocating Relationships with Hawkes Processes. - Charles Blundell; Katherine A. Heller; Jeffrey M. Beck (NIPS, 2012)

Bayesian Hierarchical Community Discovery. - Charles Blundell; Yee Whye Teh (NIPS, 2013)

Deep AutoRegressive Networks. - Karol Gregor; Ivo Danihelka; Andriy Mnih; Charles Blundell; Daan Wierstra (ICML, 2014)

The Bayesian Echo Chamber: Modeling Influence in Conversations. - Fangjian Guo; Charles Blundell; Hanna M. Wallach; Katherine A. Heller (CoRR, 2014)

The Bayesian Echo Chamber: Modeling Social Influence via Linguistic Accommodation. - Fangjian Guo; Charles Blundell; Hanna M. Wallach; Katherine A. Heller (AISTATS, 2015)

Weight Uncertainty in Neural Network. - Charles Blundell; Julien Cornebise; Koray Kavukcuoglu; Daan Wierstra (ICML, 2015)

Weight Uncertainty in Neural Networks. - Charles Blundell; Julien Cornebise; Koray Kavukcuoglu; Daan Wierstra (CoRR, 2015)

Deep Exploration via Bootstrapped DQN. - Ian Osband; Charles Blundell; Alexander Pritzel; Benjamin Van Roy (NIPS, 2016)

Matching Networks for One Shot Learning. - Oriol Vinyals; Charles Blundell; Tim Lillicrap; Koray Kavukcuoglu; Daan Wierstra (NIPS, 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)

Early Visual Concept Learning with Unsupervised Deep Learning. - Irina Higgins; Loïc Matthey; Xavier Glorot; Arka Pal; Benigno Uria; Charles Blundell; Shakir Mohamed; Alexander Lerchner (CoRR, 2016)

Learning to reinforcement learn. - Jane Wang 001; Zeb Kurth-Nelson; Hubert Soyer; Joel Z. Leibo; Dhruva Tirumala; Rémi Munos; Charles Blundell; Dharshan Kumaran; Matt M. Botvinick (CogSci, 2017)

DARLA: Improving Zero-Shot Transfer in Reinforcement Learning. - Irina Higgins; Arka Pal; Andrei A. Rusu; Loïc Matthey; Christopher P. Burgess; Alexander Pritzel; Matthew M. Botvinick; Charles Blundell; Alexander Lerchner (ICML, 2017)

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

Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles. - Balaji Lakshminarayanan; Alexander Pritzel; Charles Blundell (NIPS, 2017)

PathNet: Evolution Channels Gradient Descent in Super Neural Networks. - Chrisantha Fernando; Dylan Banarse; Charles Blundell; Yori Zwols; David Ha; Andrei A. Rusu; Alexander Pritzel; Daan Wierstra (CoRR, 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)

Bayesian Recurrent Neural Networks. - Meire Fortunato; Charles Blundell; Oriol Vinyals (CoRR, 2017)

Learning Deep Nearest Neighbor Representations Using Differentiable Boundary Trees. - Daniel Zoran; Balaji Lakshminarayanan; Charles Blundell (CoRR, 2017)

Distributed Bayesian Learning with Stochastic Natural Gradient Expectation Propagation and the Posterior Server. - Leonard Hasenclever; Stefan Webb; Thibaut Liénart; Sebastian J. Vollmer; Balaji Lakshminarayanan; Charles Blundell; Yee Whye Teh (J. Mach. Learn. Res., 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)

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)

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)

Fast deep reinforcement learning using online adjustments from the past. - Steven Hansen 001; Alexander Pritzel; Pablo Sprechmann; André Barreto 001; Charles Blundell (NeurIPS, 2018)

Pushing the bounds of dropout. - Gábor Melis; Charles Blundell; Tomás Kociský; Karl Moritz Hermann; Chris Dyer; Phil Blunsom (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)

Generalization of Reinforcement Learners with Working and Episodic Memory. - Meire Fortunato; Melissa Tan; Ryan Faulkner 001; Steven Hansen 001; Adrià Puigdomènech Badia; Gavin Buttimore; Charlie Deck; Joel Z. Leibo; Charles Blundell (NeurIPS, 2019)

Community size effect in artificial learning systems. - Olivier Tieleman; Angeliki Lazaridou; Shibl Mourad; Charles Blundell; Doina Precup (ViGIL@NeurIPS, 2019)

Shaping representations through communication: community size effect in artificial learning systems. - Olivier Tieleman; Angeliki Lazaridou; Shibl Mourad; Charles Blundell; Doina Precup (CoRR, 2019)

Never Give Up: Learning Directed Exploration Strategies. - Adrià Puigdomènech Badia; Pablo Sprechmann; Alex Vitvitskyi; Zhaohan Daniel Guo; Bilal Piot; Steven Kapturowski; Olivier Tieleman; Martín Arjovsky; Alexander Pritzel; Andrew Bolt; Charles Blundell (ICLR, 2020)

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)

Neural Execution of Graph Algorithms. - Petar Velickovic; Rex Ying; Matilde Padovano; Raia Hadsell; Charles Blundell (ICLR, 2020)

Agent57: Outperforming the Atari Human Benchmark. - Adrià Puigdomènech Badia; Bilal Piot; Steven Kapturowski; Pablo Sprechmann; Alex Vitvitskyi; Zhaohan Daniel Guo; Charles Blundell (ICML, 2020)

Pointer Graph Networks. - Petar Velickovic; Lars Buesing; Matthew C. Overlan; Razvan Pascanu; Oriol Vinyals; Charles Blundell (NeurIPS, 2020)

Object Files and Schemata: Factorizing Declarative and Procedural Knowledge in Dynamical Systems. - Anirudh Goyal; Alex Lamb; Phanideep Gampa; Philippe Beaudoin; Sergey Levine; Charles Blundell; Yoshua Bengio; Michael Mozer (CoRR, 2020)

Factorizing Declarative and Procedural Knowledge in Structured, Dynamical Environments. - Anirudh Goyal; Alex Lamb; Phanideep Gampa; Philippe Beaudoin; Charles Blundell; Sergey Levine; Yoshua Bengio; Michael Curtis Mozer (ICLR, 2021)

Representation Learning via Invariant Causal Mechanisms. - Jovana Mitrovic; Brian McWilliams; Jacob C. Walker; Lars Holger Buesing; Charles Blundell (ICLR, 2021)

Emphatic Algorithms for Deep Reinforcement Learning. - Ray Jiang; Tom Zahavy; Zhongwen Xu; Adam White 001; Matteo Hessel; Charles Blundell; Hado van Hasselt (ICML, 2021)

Neural Production Systems. - Aniket Didolkar; Anirudh Goyal; Nan Rosemary Ke; Charles Blundell; Philippe Beaudoin; Nicolas Heess; Michael Mozer; Yoshua Bengio (NeurIPS, 2021)

Coverage as a Principle for Discovering Transferable Behavior in Reinforcement Learning. - Víctor Campos 001; Pablo Sprechmann; Steven Hansen 001; André Barreto 001; Steven Kapturowski; Alex Vitvitskyi; Adrià Puigdomènech Badia; Charles Blundell (CoRR, 2021)

Persistent Message Passing. - Heiko Strathmann; Mohammadamin Barekatain; Charles Blundell; Petar Velickovic (CoRR, 2021)

PonderNet: Learning to Ponder. - Andrea Banino; Jan Balaguer; Charles Blundell (CoRR, 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)

Neural algorithmic reasoning. - Petar Velickovic; Charles Blundell (Patterns, 2021)

CoBERL: Contrastive BERT for Reinforcement Learning. - Andrea Banino; Adrià Puigdomènech Badia; Jacob C. Walker; Tim Scholtes; Jovana Mitrovic; Charles Blundell (ICLR, 2022)

Coordination Among Neural Modules Through a Shared Global Workspace. - Anirudh Goyal; Aniket Rajiv Didolkar; Alex Lamb; Kartikeya Badola; Nan Rosemary Ke; Nasim Rahaman; Jonathan Binas; Charles Blundell; Michael Curtis Mozer; Yoshua Bengio (ICLR, 2022)

Retrieval-Augmented Reinforcement Learning. - Anirudh Goyal; Abram L. Friesen; Andrea Banino; Theophane Weber; Nan Rosemary Ke; Adrià Puigdomènech Badia; Arthur Guez; Mehdi Mirza; Peter Conway Humphreys; Ksenia Konyushkova; Michal Valko; Simon Osindero; et al. (ICML, 2022)

The CLRS Algorithmic Reasoning Benchmark. - Petar Velickovic; Adrià Puigdomènech Badia; David Budden; Razvan Pascanu; Andrea Banino; Misha Dashevskiy; Raia Hadsell; Charles Blundell (ICML, 2022)

A Generalist Neural Algorithmic Learner. - Borja Ibarz; Vitaly Kurin; George Papamakarios; Kyriacos Nikiforou; Mehdi Bennani; Róbert Csordás; Andrew Joseph Dudzik; Matko Bosnjak; Alex Vitvitskyi; Yulia Rubanova; Andreea Deac; Beatrice Bevilacqua; et al. (LoG, 2022)

Reasoning-Modulated Representations. - Petar Velickovic; Matko Bosnjak; Thomas Kipf; Alexander Lerchner; Raia Hadsell; Razvan Pascanu; Charles Blundell (LoG, 2022)

Pushing the limits of self-supervised ResNets: Can we outperform supervised learning without labels on ImageNet? - Nenad Tomasev; Ioana Bica; Brian McWilliams; Lars Buesing; Razvan Pascanu; Charles Blundell; Jovana Mitrovic (CoRR, 2022)

Retrieval-Augmented Reinforcement Learning. - Anirudh Goyal; Abram L. Friesen; Andrea Banino; Theophane Weber; Nan Rosemary Ke; Adrià Puigdomènech Badia; Arthur Guez; Mehdi Mirza; Ksenia Konyushkova; Michal Valko; Simon Osindero; Timothy P. Lillicrap; et al. (CoRR, 2022)

Normalizing flows for atomic solids. - Peter Wirnsberger; George Papamakarios; Borja Ibarz; Sébastien Racanière; Andrew J. Ballard; Alexander Pritzel; Charles Blundell (Mach. Learn. Sci. Technol., 2022)

SemPPL: Predicting Pseudo-Labels for Better Contrastive Representations. - Matko Bosnjak; Pierre Harvey Richemond; Nenad Tomasev; Florian Strub; Jacob C. Walker; Felix Hill; Lars Holger Buesing; Razvan Pascanu; Charles Blundell; Jovana Mitrovic (ICLR, 2023)

Human-level Atari 200x faster. - Steven Kapturowski; Victor Campos 001; Ray Jiang; Nemanja Rakicevic; Hado van Hasselt; Charles Blundell; Adrià Puigdomènech Badia (ICLR, 2023)

Neural Algorithmic Reasoning with Causal Regularisation. - Beatrice Bevilacqua; Kyriacos Nikiforou; Borja Ibarz; Ioana Bica; Michela Paganini; Charles Blundell; Jovana Mitrovic; Petar Velickovic (ICML, 2023)

Unlocking the Power of Representations in Long-term Novelty-based Exploration. - Alaa Saade; Steven Kapturowski; Daniele Calandriello; Charles Blundell; Pablo Sprechmann; Leopoldo Sarra; Oliver Groth; Michal Valko; Bilal Piot (ICLR, 2024)

Improving fine-grained understanding in image-text pre-training. - Ioana Bica; Anastasija Ilic; Matthias Bauer; Goker Erdogan; Matko Bosnjak; Christos Kaplanis; Alexey A. Gritsenko; Matthias Minderer; Charles Blundell; Razvan Pascanu; Jovana Mitrovic (ICML, 2024)

Synth2: Boosting Visual-Language Models with Synthetic Captions and Image Embeddings. - Sahand Sharifzadeh; Christos Kaplanis; Shreya Pathak; Dharshan Kumaran; Anastasija Ilic; Jovana Mitrovic; Charles Blundell; Andrea Banino (CoRR, 2024)

The CLRS-Text Algorithmic Reasoning Language Benchmark. - Larisa Markeeva; Sean McLeish; Borja Ibarz; Wilfried Bounsi; Olga Kozlova; Alex Vitvitskyi; Charles Blundell; Tom Goldstein; Avi Schwarzschild; Petar Velickovic (CoRR, 2024)