Diane Bouchacourt

According to our database, Diane Bouchacourt authored at least 39 papers between 2015 and 2024.

Collaborative distances:

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

2024

Reassessing the Validity of Spurious Correlations Benchmarks.

Samuel J. Bell, Diane Bouchacourt, Levent Sagun

CoRR, 2024

UniBench: Visual Reasoning Requires Rethinking Vision-Language Beyond Scaling.

Haider Al-Tahan, Quentin Garrido, Randall Balestriero, Diane Bouchacourt, Caner Hazirbas, Mark Ibrahim

CoRR, 2024

𝕏-Sample Contrastive Loss: Improving Contrastive Learning with Sample Similarity Graphs.

Vlad Sobal, Mark Ibrahim, Randall Balestriero, Vivien Cabannes, Diane Bouchacourt, Pietro Astolfi, Kyunghyun Cho, Yann LeCun

CoRR, 2024

The Factorization Curse: Which Tokens You Predict Underlie the Reversal Curse and More.

Ouail Kitouni, Niklas Nolte, Diane Bouchacourt, Adina Williams, Mike Rabbat, Mark Ibrahim

CoRR, 2024

An Introduction to Vision-Language Modeling.

Florian Bordes, Richard Yuanzhe Pang, Anurag Ajay, Alexander C. Li, Adrien Bardes, Suzanne Petryk, Oscar Mañas, Zhiqiu Lin, Anas Mahmoud, Bargav Jayaraman, Mark Ibrahim, Melissa Hall, Yunyang Xiong, Jonathan Lebensold, Candace Ross, Srihari Jayakumar, Chuan Guo, Diane Bouchacourt, Haider Al-Tahan, Karthik Padthe, Vasu Sharma, Hu Xu, Xiaoqing Ellen Tan, Megan Richards, Samuel Lavoie, Pietro Astolfi, Reyhane Askari Hemmat, Jun Chen, Kushal Tirumala, Rim Assouel, Mazda Moayeri, Arjang Talattof, Kamalika Chaudhuri, Zechun Liu, Xilun Chen, Quentin Garrido, Karen Ullrich, Aishwarya Agrawal, Kate Saenko, Asli Celikyilmaz, Vikas Chandra

CoRR, 2024

Discovering Environments with XRM.

Mohammad Pezeshki, Diane Bouchacourt, Mark Ibrahim, Nicolas Ballas, Pascal Vincent, David Lopez-Paz

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Does Progress On Object Recognition Benchmarks Improve Generalization on Crowdsourced, Global Data?

Megan Richards, Polina Kirichenko, Diane Bouchacourt, Mark Ibrahim

Proceedings of the Twelfth International Conference on Learning Representations, 2024

Embracing Diversity: Interpretable Zero-shot Classification Beyond One Vector Per Class.

Mazda Moayeri, Michael Rabbat, Mark Ibrahim, Diane Bouchacourt

Proceedings of the 2024 ACM Conference on Fairness, Accountability, and Transparency, 2024

2023

The Robustness Limits of SoTA Vision Models to Natural Variation.

Mark Ibrahim, Quentin Garrido, Ari S. Morcos, Diane Bouchacourt

Trans. Mach. Learn. Res., 2023

Self-Supervised Disentanglement by Leveraging Structure in Data Augmentations.

Cian Eastwood, Julius von Kügelgen, Linus Ericsson, Diane Bouchacourt, Pascal Vincent, Bernhard Schölkopf, Mark Ibrahim

CoRR, 2023

Does Progress On Object Recognition Benchmarks Improve Real-World Generalization?

Megan Richards, Polina Kirichenko, Diane Bouchacourt, Mark Ibrahim

CoRR, 2023

Pinpointing Why Object Recognition Performance Degrades Across Income Levels and Geographies.

Laura Gustafson, Megan Richards, Melissa Hall, Caner Hazirbas, Diane Bouchacourt, Mark Ibrahim

CoRR, 2023

Understanding the detrimental class-level effects of data augmentation.

Polina Kirichenko, Mark Ibrahim, Randall Balestriero, Diane Bouchacourt, Shanmukha Ramakrishna Vedantam, Hamed Firooz, Andrew Gordon Wilson

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

Exploring Why Object Recognition Performance Degrades Across Income Levels and Geographies with Factor Annotations.

Laura Gustafson, Megan Richards, Melissa Hall, Caner Hazirbas, Diane Bouchacourt, Mark Ibrahim

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

PUG: Photorealistic and Semantically Controllable Synthetic Data for Representation Learning.

Florian Bordes, Shashank Shekhar, Mark Ibrahim, Diane Bouchacourt, Pascal Vincent, Ari Morcos

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

Birth of a Transformer: A Memory Viewpoint.

Alberto Bietti, Vivien Cabannes, Diane Bouchacourt, Hervé Jégou, Léon Bottou

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

Disentanglement of Correlated Factors via Hausdorff Factorized Support.

Karsten Roth, Mark Ibrahim, Zeynep Akata, Pascal Vincent, Diane Bouchacourt

Proceedings of the Eleventh International Conference on Learning Representations, 2023

ImageNet-X: Understanding Model Mistakes with Factor of Variation Annotations.

Badr Youbi Idrissi, Diane Bouchacourt, Randall Balestriero, Ivan Evtimov, Caner Hazirbas, Nicolas Ballas, Pascal Vincent, Michal Drozdzal, David Lopez-Paz, Mark Ibrahim

Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022

Robust Self-Supervised Learning with Lie Groups.

Mark Ibrahim, Diane Bouchacourt, Ari S. Morcos

CoRR, 2022

Measuring and signing fairness as performance under multiple stakeholder distributions.

David Lopez-Paz, Diane Bouchacourt, Levent Sagun, Nicolas Usunier

CoRR, 2022

2021

Addressing the Topological Defects of Disentanglement via Distributed Operators.

Diane Bouchacourt, Mark Ibrahim, Stéphane Deny

CoRR, 2021

Grounding inductive biases in natural images: invariance stems from variations in data.

Diane Bouchacourt, Mark Ibrahim, Ari S. Morcos

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

2020

Think before you act: A simple baseline for compositional generalization.

Christina Heinze-Deml, Diane Bouchacourt

CoRR, 2020

A Benchmark for Systematic Generalization in Grounded Language Understanding.

Laura Ruis, Jacob Andreas, Marco Baroni, Diane Bouchacourt, Brenden M. Lake

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

Entropy Minimization In Emergent Languages.

Eugene Kharitonov, Rahma Chaabouni, Diane Bouchacourt, Marco Baroni

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

Permutation Equivariant Models for Compositional Generalization in Language.

Jonathan Gordon, David Lopez-Paz, Marco Baroni, Diane Bouchacourt

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

Compositionality and Generalization In Emergent Languages.

Rahma Chaabouni, Eugene Kharitonov, Diane Bouchacourt, Emmanuel Dupoux, Marco Baroni

Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, 2020

2019

Focus on What's Informative and Ignore What's not: Communication Strategies in a Referential Game.

Roberto Dessì, Diane Bouchacourt, Davide Crepaldi, Marco Baroni

CoRR, 2019

Mastering emergent language: learning to guide in simulated navigation.

Mathijs Mul, Diane Bouchacourt, Elia Bruni

CoRR, 2019

Information Minimization In Emergent Languages.

Eugene Kharitonov, Rahma Chaabouni, Diane Bouchacourt, Marco Baroni

CoRR, 2019

EDUCE: Explaining model Decisions through Unsupervised Concepts Extraction.

Diane Bouchacourt, Ludovic Denoyer

CoRR, 2019

EGG: a toolkit for research on Emergence of lanGuage in Games.

Eugene Kharitonov, Rahma Chaabouni, Diane Bouchacourt, Marco Baroni

Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing, 2019

Miss Tools and Mr Fruit: Emergent Communication in Agents Learning about Object Affordances.

Diane Bouchacourt, Marco Baroni

Proceedings of the 57th Conference of the Association for Computational Linguistics, 2019

2018

How agents see things: On visual representations in an emergent language game.

Diane Bouchacourt, Marco Baroni

Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, Brussels, Belgium, October 31, 2018

Multi-Level Variational Autoencoder: Learning Disentangled Representations From Grouped Observations.

Diane Bouchacourt, Ryota Tomioka, Sebastian Nowozin

Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018

2017

Task-oriented learning of structured probability distributions.

Diane Bouchacourt

PhD thesis, 2017

2016

DISCO Nets: DISsimilarity COefficient Networks.

Diane Bouchacourt, M. Pawan Kumar, Sebastian Nowozin

CoRR, 2016

DISCO Nets : DISsimilarity COefficients Networks.

Diane Bouchacourt, Pawan Kumar Mudigonda, Sebastian Nowozin

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

2015

Entropy-Based Latent Structured Output Prediction.

Diane Bouchacourt, Sebastian Nowozin, M. Pawan Kumar

Proceedings of the 2015 IEEE International Conference on Computer Vision, 2015