Vivien Cabannes
POSTDOCTORAL RESEARCHER | NEW YORK CITY, UNITED STATES
Vivien Cabannes is a researcher in core machine learning. His interests include learning with few human annotations (weakly supervised learning, representation learning, active learning), as well as understanding the inner workings of deployed machine learning methods.
Research Areas
Vivien's Publications
July 24, 2024
COMPUTER VISION
X-Sample Contrastive Loss: Improving Contrastive Learning with Sample Similarity Graphs
Vlad Sobal, Mark Ibrahim, Randall Balestriero, Vivien Cabannes, Pietro Astolfi, Kyunghyun Cho, Yann LeCun
July 24, 2024
October 05, 2023
CORE MACHINE LEARNING
Active Self-Supervised Learning: A Few Low-Cost Relationships Are All You Need
Vivien Cabannes, Leon Bottou, Yann LeCun, Randall Balestriero
October 05, 2023
June 26, 2023
CORE MACHINE LEARNING
The SSL Interplay: Augmentations, Inductive Bias, and Generalization
Vivien Cabannes, Bobak Kiani, Randall Balestriero, Yann LeCun, Alberto Bietti
June 26, 2023
Foundational models
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