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

Florian Bordes, Richard 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, Ellen Tan, Megan Richards, Samuel Lavoie, Pietro Astolfi, Reyhane Askari, 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