3 citations · 5 across the 11 of their papers we have counts for
Showing 2024Show all
3 papers · 1 filter
cs.LG2024
Understanding the Role of Equivariance in Self-supervised Learning
Yifei Wang, Kaiwen Hu, Sharut Gupta +3
Contrastive learning has been a leading paradigm for self-supervised learning, but it is widely observed that it comes at the price of sacrificing useful features (\eg colors) by b…
cs.LG2024
An Information Criterion for Controlled Disentanglement of Multimodal Data
Chenyu Wang, Sharut Gupta, Xinyi Zhang +4
Multimodal representation learning seeks to relate and decompose information inherent in multiple modalities. By disentangling modality-specific information from information that i…
cs.LG2024
In-Context Symmetries: Self-Supervised Learning through Contextual World Models
Sharut Gupta, Chenyu Wang, Yifei Wang +2
At the core of self-supervised learning for vision is the idea of learning invariant or equivariant representations with respect to a set of data transformations. This approach, ho…