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Encoders and Ensembles for Task-Free Continual Learning

May 27, 2021
Murray Shanahan, Christos Kaplanis, Jovana Mitrović

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Unsupervised Object-Based Transition Models for 3D Partially Observable Environments

Mar 08, 2021
Antonia Creswell, Rishabh Kabra, Chris Burgess, Murray Shanahan

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AlignNet: Unsupervised Entity Alignment

Jul 21, 2020
Antonia Creswell, Kyriacos Nikiforou, Oriol Vinyals, Andre Saraiva, Rishabh Kabra, Loic Matthey, Chris Burgess, Malcolm Reynolds, Richard Tanburn, Marta Garnelo, Murray Shanahan

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Learning to Combine Top-Down and Bottom-Up Signals in Recurrent Neural Networks with Attention over Modules

Jun 30, 2020
Sarthak Mittal, Alex Lamb, Anirudh Goyal, Vikram Voleti, Murray Shanahan, Guillaume Lajoie, Michael Mozer, Yoshua Bengio

* ICML 2020 

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Learning Diverse Representations for Fast Adaptation to Distribution Shift

Jun 12, 2020
Daniel Pace, Alessandra Russo, Murray Shanahan

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Systematic Generalisation through Task Temporal Logic and Deep Reinforcement Learning

Jun 12, 2020
Borja G. Leon, Murray Shanahan, Francesco Belardinelli

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Continual Reinforcement Learning with Multi-Timescale Replay

Apr 16, 2020
Christos Kaplanis, Claudia Clopath, Murray Shanahan

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The Animal-AI Environment: Training and Testing Animal-Like Artificial Cognition

Sep 18, 2019
Benjamin Beyret, José Hernández-Orallo, Lucy Cheke, Marta Halina, Murray Shanahan, Matthew Crosby

* 14 pages, 34 figures (update: reduce images size) 

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An Explicitly Relational Neural Network Architecture

May 24, 2019
Murray Shanahan, Kyriacos Nikiforou, Antonia Creswell, Christos Kaplanis, David Barrett, Marta Garnelo

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Policy Consolidation for Continual Reinforcement Learning

Feb 01, 2019
Christos Kaplanis, Murray Shanahan, Claudia Clopath

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Consistent Jumpy Predictions for Videos and Scenes

Oct 02, 2018
Ananya Kumar, S. M. Ali Eslami, Danilo J. Rezende, Marta Garnelo, Fabio Viola, Edward Lockhart, Murray Shanahan

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Conditional Neural Processes

Jul 04, 2018
Marta Garnelo, Dan Rosenbaum, Chris J. Maddison, Tiago Ramalho, David Saxton, Murray Shanahan, Yee Whye Teh, Danilo J. Rezende, S. M. Ali Eslami

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Relational Deep Reinforcement Learning

Jun 28, 2018
Vinicius Zambaldi, David Raposo, Adam Santoro, Victor Bapst, Yujia Li, Igor Babuschkin, Karl Tuyls, David Reichert, Timothy Lillicrap, Edward Lockhart, Murray Shanahan, Victoria Langston, Razvan Pascanu, Matthew Botvinick, Oriol Vinyals, Peter Battaglia

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Continual Reinforcement Learning with Complex Synapses

Jun 19, 2018
Christos Kaplanis, Murray Shanahan, Claudia Clopath

* Accepted at ICML 2018 

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SCAN: Learning Hierarchical Compositional Visual Concepts

Jun 06, 2018
Irina Higgins, Nicolas Sonnerat, Loic Matthey, Arka Pal, Christopher P Burgess, Matko Bosnjak, Murray Shanahan, Matthew Botvinick, Demis Hassabis, Alexander Lerchner

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Feature Control as Intrinsic Motivation for Hierarchical Reinforcement Learning

Nov 22, 2017
Nat Dilokthanakul, Christos Kaplanis, Nick Pawlowski, Murray Shanahan

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Classifying Options for Deep Reinforcement Learning

Jun 19, 2017
Kai Arulkumaran, Nat Dilokthanakul, Murray Shanahan, Anil Anthony Bharath

* IJCAI 2016 Workshop on Deep Reinforcement Learning: Frontiers and Challenges 

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Deep Unsupervised Clustering with Gaussian Mixture Variational Autoencoders

Jan 13, 2017
Nat Dilokthanakul, Pedro A. M. Mediano, Marta Garnelo, Matthew C. H. Lee, Hugh Salimbeni, Kai Arulkumaran, Murray Shanahan

* 12 pages, 6 figures, Under review as a conference paper at ICLR 2017 

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Towards Deep Symbolic Reinforcement Learning

Oct 01, 2016
Marta Garnelo, Kai Arulkumaran, Murray Shanahan

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Ascribing Consciousness to Artificial Intelligence

Sep 05, 2015
Murray Shanahan

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