13 citations · 35 across the 6 of their papers we have counts for
Showing 2021Show all
3 papers · 1 filter
cs.LG2021★ 11 cited
Drop, Swap, and Generate: A Self-Supervised Approach for Generating Neural Activity
Ran Liu, Mehdi Azabou, Max Dabagia +5
Meaningful and simplified representations of neural activity can yield insights into how and what information is being processed within a neural circuit. However, without labels, f…
cs.LG2021★ 10 cited
Understand and Improve Contrastive Learning Methods for Visual Representation: A Review
Ran Liu
Traditional supervised learning methods are hitting a bottleneck because of their dependency on expensive manually labeled data and their weaknesses such as limited generalization…
cs.LG2021★ 13 cited
Mine Your Own vieW: Self-Supervised Learning Through Across-Sample Prediction
Mehdi Azabou, Mohammad Gheshlaghi Azar, Ran Liu +10
State-of-the-art methods for self-supervised learning (SSL) build representations by maximizing the similarity between different transformed "views" of a sample. Without sufficient…