Arthur Mensch

According to our database, Arthur Mensch authored at least 32 papers between 2014 and 2024.

Collaborative distances:

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

2024

Mixtral of Experts.

Albert Q. Jiang, Alexandre Sablayrolles, Antoine Roux, Arthur Mensch, Blanche Savary, Chris Bamford, Devendra Singh Chaplot, Diego de Las Casas, Emma Bou Hanna, Florian Bressand, Gianna Lengyel, Guillaume Bour, Guillaume Lample, Lélio Renard Lavaud, Lucile Saulnier, Marie-Anne Lachaux, Pierre Stock, Sandeep Subramanian, Sophia Yang, Szymon Antoniak, Teven Le Scao, Théophile Gervet, Thibaut Lavril, Thomas Wang, Timothée Lacroix, William El Sayed

CoRR, 2024

2023

Mistral 7B.

Albert Q. Jiang, Alexandre Sablayrolles, Arthur Mensch, Chris Bamford, Devendra Singh Chaplot, Diego de Las Casas, Florian Bressand, Gianna Lengyel, Guillaume Lample, Lucile Saulnier, Lélio Renard Lavaud, Marie-Anne Lachaux, Pierre Stock, Teven Le Scao, Thibaut Lavril, Thomas Wang, Timothée Lacroix, William El Sayed

CoRR, 2023

Three ways to improve feature alignment for open vocabulary detection.

Relja Arandjelovic, Alex Andonian, Arthur Mensch, Olivier J. Hénaff, Jean-Baptiste Alayrac, Andrew Zisserman

CoRR, 2023

2022

Self-conditioned Embedding Diffusion for Text Generation.

Robin Strudel, Corentin Tallec, Florent Altché, Yilun Du, Yaroslav Ganin, Arthur Mensch, Will Grathwohl, Nikolay Savinov, Sander Dieleman, Laurent Sifre, Rémi Leblond

CoRR, 2022

Dissecting adaptive methods in GANs.

Samy Jelassi, David Dobre, Arthur Mensch, Yuanzhi Li, Gauthier Gidel

CoRR, 2022

Flamingo: a Visual Language Model for Few-Shot Learning.

Jean-Baptiste Alayrac, Jeff Donahue, Pauline Luc, Antoine Miech, Iain Barr, Yana Hasson, Karel Lenc, Arthur Mensch, Katie Millican, Malcolm Reynolds, Roman Ring, Eliza Rutherford, Serkan Cabi, Tengda Han, Zhitao Gong, Sina Samangooei, Marianne Monteiro, Jacob Menick, Sebastian Borgeaud, Andrew Brock, Aida Nematzadeh, Sahand Sharifzadeh, Mikolaj Binkowski, Ricardo Barreira, Oriol Vinyals, Andrew Zisserman, Karen Simonyan

CoRR, 2022

Training Compute-Optimal Large Language Models.

Jordan Hoffmann, Sebastian Borgeaud, Arthur Mensch, Elena Buchatskaya, Trevor Cai, Eliza Rutherford, Diego de Las Casas, Lisa Anne Hendricks, Johannes Welbl, Aidan Clark, Tom Hennigan, Eric Noland, Katie Millican, George van den Driessche, Bogdan Damoc, Aurelia Guy, Simon Osindero, Karen Simonyan, Erich Elsen, Jack W. Rae, Oriol Vinyals, Laurent Sifre

CoRR, 2022

Unified Scaling Laws for Routed Language Models.

Aidan Clark, Diego de Las Casas, Aurelia Guy, Arthur Mensch, Michela Paganini, Jordan Hoffmann, Bogdan Damoc, Blake A. Hechtman, Trevor Cai, Sebastian Borgeaud, George van den Driessche, Eliza Rutherford, Tom Hennigan, Matthew J. Johnson, Katie Millican, Albin Cassirer, Chris Jones, Elena Buchatskaya, David Budden, Laurent Sifre, Simon Osindero, Oriol Vinyals, Jack W. Rae, Erich Elsen, Koray Kavukcuoglu, Karen Simonyan

CoRR, 2022

An empirical analysis of compute-optimal large language model training.

Jordan Hoffmann, Sebastian Borgeaud, Arthur Mensch, Elena Buchatskaya, Trevor Cai, Eliza Rutherford, Diego de Las Casas, Lisa Anne Hendricks, Johannes Welbl, Aidan Clark, Tom Hennigan, Eric Noland, Katherine Millican, George van den Driessche, Bogdan Damoc, Aurelia Guy, Simon Osindero, Karen Simonyan, Erich Elsen, Oriol Vinyals, Jack W. Rae, Laurent Sifre

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Flamingo: a Visual Language Model for Few-Shot Learning.

Jean-Baptiste Alayrac, Jeff Donahue, Pauline Luc, Antoine Miech, Iain Barr, Yana Hasson, Karel Lenc, Arthur Mensch, Katherine Millican, Malcolm Reynolds, Roman Ring, Eliza Rutherford, Serkan Cabi, Tengda Han, Zhitao Gong, Sina Samangooei, Marianne Monteiro, Jacob L. Menick, Sebastian Borgeaud, Andy Brock, Aida Nematzadeh, Sahand Sharifzadeh, Mikolaj Binkowski, Ricardo Barreira, Oriol Vinyals, Andrew Zisserman, Karén Simonyan

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Unified Scaling Laws for Routed Language Models.

Aidan Clark, Diego de Las Casas, Aurelia Guy, Arthur Mensch, Michela Paganini, Jordan Hoffmann, Bogdan Damoc, Blake A. Hechtman, Trevor Cai, Sebastian Borgeaud, George van den Driessche, Eliza Rutherford, Tom Hennigan, Matthew J. Johnson, Albin Cassirer, Chris Jones, Elena Buchatskaya, David Budden, Laurent Sifre, Simon Osindero, Oriol Vinyals, Marc'Aurelio Ranzato, Jack W. Rae, Erich Elsen, Koray Kavukcuoglu, Karen Simonyan

Proceedings of the International Conference on Machine Learning, 2022

Improving Language Models by Retrieving from Trillions of Tokens.

Sebastian Borgeaud, Arthur Mensch, Jordan Hoffmann, Trevor Cai, Eliza Rutherford, Katie Millican, George van den Driessche, Jean-Baptiste Lespiau, Bogdan Damoc, Aidan Clark, Diego de Las Casas, Aurelia Guy, Jacob Menick, Roman Ring, Tom Hennigan, Saffron Huang, Loren Maggiore, Chris Jones, Albin Cassirer, Andy Brock, Michela Paganini, Geoffrey Irving, Oriol Vinyals, Simon Osindero, Karen Simonyan, Jack W. Rae, Erich Elsen, Laurent Sifre

Proceedings of the International Conference on Machine Learning, 2022

2021

Extracting representations of cognition across neuroimaging studies improves brain decoding.

Arthur Mensch, Julien Mairal, Bertrand Thirion, Gaël Varoquaux

PLoS Comput. Biol., 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, Jacob Menick, Albin Cassirer, Richard Powell, George van den Driessche, Lisa Anne Hendricks, Maribeth Rauh, Po-Sen Huang, Amelia Glaese, Johannes Welbl, Sumanth Dathathri, Saffron Huang, Jonathan Uesato, John Mellor, Irina Higgins, Antonia Creswell, Nat McAleese, Amy Wu, Erich Elsen, Siddhant M. Jayakumar, Elena Buchatskaya, David Budden, Esme Sutherland, Karen Simonyan, Michela Paganini, Laurent Sifre, Lena Martens, Xiang Lorraine Li, Adhiguna Kuncoro, Aida Nematzadeh, Elena Gribovskaya, Domenic Donato, Angeliki Lazaridou, Arthur Mensch, Jean-Baptiste Lespiau, Maria Tsimpoukelli, Nikolai Grigorev, Doug Fritz, Thibault Sottiaux, Mantas Pajarskas, Toby Pohlen, Zhitao Gong, Daniel Toyama, Cyprien de Masson d'Autume, Yujia Li, Tayfun Terzi, Vladimir Mikulik, Igor Babuschkin, Aidan Clark, Diego de Las Casas, Aurelia Guy, Chris Jones, James Bradbury, Matthew J. Johnson, Blake A. Hechtman, Laura Weidinger, Iason Gabriel, William Isaac, Edward Lockhart, Simon Osindero, Laura Rimell, Chris Dyer, Oriol Vinyals, Kareem Ayoub, Jeff Stanway, Lorrayne Bennett, Demis Hassabis, Koray Kavukcuoglu, Geoffrey Irving

CoRR, 2021

Differentiable Divergences Between Time Series.

Mathieu Blondel, Arthur Mensch, Jean-Philippe Vert

Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

2020

International electronic health record-derived COVID-19 clinical course profiles: the 4CE consortium.

Gabriel A. Brat, Griffin M. Weber, Nils Gehlenborg, Paul Avillach, Nathan P. Palmer, Luca Chiovato, James J. Cimino, Lemuel R. Waitman, Gilbert S. Omenn, Alberto Malovini, Jason H. Moore, Brett K. Beaulieu-Jones, Valentina Tibollo, Shawn N. Murphy, Sehi L'Yi, Mark S. Keller, Riccardo Bellazzi, David A. Hanauer, Arnaud Serret-Larmande, Alba Gutiérrez-Sacristán, John J. Holmes, Douglas S. Bell, Kenneth D. Mandl, Robert W. Follett, Jeffrey G. Klann, Douglas A. Murad, Luigia Scudeller, Mauro Bucalo, Katie G. Kirchoff, Jean B. Craig, Jihad S. Obeid, Vianney Jouhet, Romain Griffier, Sébastien Cossin, Bertrand Moal, Lav P. Patel, Antonio Bellasi, Hans-Ulrich Prokosch, Detlef Kraska, Piotr Sliz, Amelia L. M. Tan, Kee Yuan Ngiam, Alberto Zambelli, Danielle L. Mowery, Emily Schriver, Batsal Devkota, Robert L. Bradford, Mohamad Daniar, Christel Daniel, Vincent Benoit, Romain Bey, Nicolas Paris, Patricia Serre, Nina Orlova, Julien Dubiel, Martin Hilka, Anne-Sophie Jannot, Stéphane Bréant, Judith Leblanc, Nicolas Griffon, Anita Burgun, Mélodie Bernaux, Arnaud Sandrin, Elisa Salamanca, Sylvie Cormont, Thomas Ganslandt, Tobias Gradinger, Julien Champ, Martin Boeker, Patricia Martel, Loic Esteve, Alexandre Gramfort, Olivier Grisel, Damien Leprovost, Thomas Moreau, Gaël Varoquaux, Jill-Jênn Vie, Demian Wassermann, Arthur Mensch, Charlotte Caucheteux, Christian Haverkamp, Guillaume Lemaitre, Silvano Bosari, Ian D. Krantz, Andrew M. South, Tianxi Cai, Isaac S. Kohane

npj Digit. Medicine, 2020

Fine-grain atlases of functional modes for fMRI analysis.

Kamalaker Dadi, Gaël Varoquaux, Antonia Machlouzarides-Shalit, Krzysztof J. Gorgolewski, Demian Wassermann, Bertrand Thirion, Arthur Mensch

NeuroImage, 2020

Online Sinkhorn: Optimal Transport distances from sample streams.

Arthur Mensch, Gabriel Peyré

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

A mean-field analysis of two-player zero-sum games.

Carles Domingo-Enrich, Samy Jelassi, Arthur Mensch, Grant M. Rotskoff, Joan Bruna

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Extra-gradient with player sampling for faster convergence in n-player games.

Samy Jelassi, Carles Domingo-Enrich, Damien Scieur, Arthur Mensch, Joan Bruna

Proceedings of the 37th International Conference on Machine Learning, 2020

2019

Extra-gradient with player sampling for provable fast convergence in n-player games.

Samy Jelassi, Carles Domingo-Enrich, Damien Scieur, Arthur Mensch, Joan Bruna

CoRR, 2019

Geometric Losses for Distributional Learning.

Arthur Mensch, Mathieu Blondel, Gabriel Peyré

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

2018

Stochastic Subsampling for Factorizing Huge Matrices.

Arthur Mensch, Julien Mairal, Bertrand Thirion, Gaël Varoquaux

IEEE Trans. Signal Process., 2018

Extracting Universal Representations of Cognition across Brain-Imaging Studies.

Arthur Mensch, Julien Mairal, Bertrand Thirion, Gaël Varoquaux

CoRR, 2018

Differentiable Dynamic Programming for Structured Prediction and Attention.

Arthur Mensch, Mathieu Blondel

Proceedings of the 35th International Conference on Machine Learning, 2018

2017

Subsampling Enables Fast Factorisation of Huge Matrices into Sparse Signals.

Arthur Mensch, Julien Mairal, Bertrand Thirion, Gaël Varoquaux

ERCIM News, 2017

Learning Neural Representations of Human Cognition across Many fMRI Studies.

Arthur Mensch, Julien Mairal, Danilo Bzdok, Bertrand Thirion, Gaël Varoquaux

Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

2016

Compressed Online Dictionary Learning for Fast fMRI Decomposition.

Arthur Mensch, Gaël Varoquaux, Bertrand Thirion

CoRR, 2016

Learning brain regions via large-scale online structured sparse dictionary learning.

Elvis Dohmatob, Arthur Mensch, Gaël Varoquaux, Bertrand Thirion

Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Compressed online dictionary learning for fast resting-state fMRI decomposition.

Arthur Mensch, Gaël Varoquaux, Bertrand Thirion

Proceedings of the 13th IEEE International Symposium on Biomedical Imaging, 2016

Dictionary Learning for Massive Matrix Factorization.

Arthur Mensch, Julien Mairal, Bertrand Thirion, Gaël Varoquaux

Proceedings of the 33nd International Conference on Machine Learning, 2016

2014

Connection Forms for Beating the Heart - LV Mechanics Challenge (Methods).

Arthur Mensch, Emmanuel Piuze, Lucas Lehnert, Adrianus J. Bakermans, Jon Sporring, Gustav J. Strijkers, Kaleem Siddiqi

Proceedings of the Statistical Atlases and Computational Models of the Heart - Imaging and Modelling Challenges, 2014