Loïc Matthey

According to our database, Loïc Matthey authored at least 27 papers between 2008 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2023

SODA: Bottleneck Diffusion Models for Representation Learning.

Drew A. Hudson, Daniel Zoran, Mateusz Malinowski, Andrew K. Lampinen, Andrew Jaegle, James L. McClelland, Loic Matthey, Felix Hill, Alexander Lerchner

CoRR, 2023

Evaluating VLMs for Score-Based, Multi-Probe Annotation of 3D Objects.

Rishabh Kabra, Loic Matthey, Alexander Lerchner, Niloy J. Mitra

CoRR, 2023

Combining Behaviors with the Successor Features Keyboard.

Wilka Carvalho, Andre Saraiva, Angelos Filos, Andrew K. Lampinen, Loic Matthey, Richard L. Lewis, Honglak Lee, Satinder Singh, Danilo Jimenez Rezende, Daniel Zoran

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

2021

Constellation: Learning relational abstractions over objects for compositional imagination.

James C. R. Whittington, Rishabh Kabra, Loic Matthey, Christopher P. Burgess, Alexander Lerchner

CoRR, 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, Neil C. Rabinowitz, Loic Matthey, Demis Hassabis, Alexander Lerchner, Matthew M. Botvinick

CoRR, 2021

SIMONe: View-Invariant, Temporally-Abstracted Object Representations via Unsupervised Video Decomposition.

Rishabh Kabra, Daniel Zoran, Goker Erdogan, Loic Matthey, Antonia Creswell, Matt M. Botvinick, Alexander Lerchner, Christopher P. Burgess

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

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

Jane Wang, 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, Neil C. Rabinowitz, Loic Matthey, Demis Hassabis, Alexander Lerchner, Matt M. Botvinick

Proceedings of the Neural Information Processing Systems Track on Datasets and Benchmarks 1, 2021

2020

AlignNet: Unsupervised Entity Alignment.

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

CoRR, 2020

Unsupervised Model Selection for Variational Disentangled Representation Learning.

Sunny Duan, Loic Matthey, Andre Saraiva, Nick Watters, Chris Burgess, Alexander Lerchner, Irina Higgins

Proceedings of the 8th International Conference on Learning Representations, 2020

2019

A Heuristic for Unsupervised Model Selection for Variational Disentangled Representation Learning.

Sunny Duan, Nicholas Watters, Loic Matthey, Chris Burgess, Alexander Lerchner, Irina Higgins

CoRR, 2019

COBRA: Data-Efficient Model-Based RL through Unsupervised Object Discovery and Curiosity-Driven Exploration.

Nicholas Watters, Loic Matthey, Matko Bosnjak, Christopher P. Burgess, Alexander Lerchner

CoRR, 2019

MONet: Unsupervised Scene Decomposition and Representation.

Christopher P. Burgess, Loïc Matthey, Nicholas Watters, Rishabh Kabra, Irina Higgins, Matthew M. Botvinick, Alexander Lerchner

CoRR, 2019

Spatial Broadcast Decoder: A Simple Architecture for Learning Disentangled Representations in VAEs.

Nicholas Watters, Loïc Matthey, Christopher P. Burgess, Alexander Lerchner

CoRR, 2019

Multi-Object Representation Learning with Iterative Variational Inference.

Klaus Greff, Raphaël Lopez Kaufman, Rishabh Kabra, Nick Watters, Chris Burgess, Daniel Zoran, Loic Matthey, Matthew M. Botvinick, Alexander Lerchner

Proceedings of the 36th International Conference on Machine Learning, 2019

2018

Towards a Definition of Disentangled Representations.

Irina Higgins, David Amos, David Pfau, Sébastien Racanière, Loïc Matthey, Danilo J. Rezende, Alexander Lerchner

CoRR, 2018

Understanding disentangling in β-VAE.

Christopher P. Burgess, Irina Higgins, Arka Pal, Loïc Matthey, Nick Watters, Guillaume Desjardins, Alexander Lerchner

CoRR, 2018

Life-Long Disentangled Representation Learning with Cross-Domain Latent Homologies.

Alessandro Achille, Tom Eccles, Loïc Matthey, Christopher P. Burgess, Nicholas Watters, Alexander Lerchner, Irina Higgins

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 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

Proceedings of the 6th International Conference on Learning Representations, 2018

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

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

Proceedings of the 34th International Conference on Machine Learning, 2017

beta-VAE: Learning Basic Visual Concepts with a Constrained Variational Framework.

Irina Higgins, Loïc Matthey, Arka Pal, Christopher P. Burgess, Xavier Glorot, Matthew M. Botvinick, Shakir Mohamed, Alexander Lerchner

Proceedings of the 5th International Conference on Learning Representations, 2017

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

2015

A Probabilistic Palimpsest Model of Visual Short-term Memory.

Loic Matthey, Paul M. Bays, Peter Dayan

PLoS Comput. Biol., 2015

2010

Aggregation-mediated collective perception and action in a group of miniature robots.

Grégory Mermoud, Loïc Matthey, William C. Evans, Alcherio Martinoli

Proceedings of the 9th International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2010), 2010

2009

Stochastic strategies for a swarm robotic assembly system.

Loic Matthey, Spring Berman, Vijay Kumar

Proceedings of the 2009 IEEE International Conference on Robotics and Automation, 2009

2008

Experimental study of limit cycle and chaotic controllers for the locomotion of centipede robots.

Loic Matthey, Ludovic Righetti, Auke Jan Ijspeert

Proceedings of the 2008 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2008

A comparison of casting and spiraling algorithms for odor source localization in laminar flow.

Thomas Lochmatter, Xavier Raemy, Loïc Matthey, Saurabh Indra, Alcherio Martinoli

Proceedings of the 2008 IEEE International Conference on Robotics and Automation, 2008