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Diane Bouchacourt

RESEARCH SCIENTIST | PARIS, FRANCE

Diane is a research scientist at Facebook AI Research (FAIR), focusing on representation learning and unsupervised/weakly supervised learning. She is interested in building robust models by using group theory and disentanglement methods. Diane earned her Ph.D. in machine learning at the University of Oxford.

Research Areas

Computer Vision

Core Machine Learning

Natural Language Processing (NLP)

Diane's Work

Think before you act: A simple baseline for compositional generalization

Multi-Level Variational Autoencoder: Learning Disentangled Representations from Grouped Observations 32nd AAAI Conference on Artificial Intelligence (AAAI 2018)

Diane's Publications

June 05, 2024

CORE MACHINE LEARNING

An Introduction to Vision-Language Modeling

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