785 citations · 907 across the 9 of their papers we have counts for
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cs.CV2023★ 4 cited
Blockwise Self-Supervised Learning at Scale
Shoaib Ahmed Siddiqui, David Krueger, Yann LeCun +1
Current state-of-the-art deep networks are all powered by backpropagation. In this paper, we explore alternatives to full backpropagation in the form of blockwise learning rules, l…
cs.CV2022
Progress and limitations of deep networks to recognize objects in unusual poses
Amro Abbas, Stéphane Deny
Deep networks should be robust to rare events if they are to be successfully deployed in high-stakes real-world applications (e.g., self-driving cars). Here we study the capability…
cs.CV2021★ 785 cited
Barlow Twins: Self-Supervised Learning via Redundancy Reduction
Jure Zbontar, Li Jing, Ishan Misra +2
Self-supervised learning (SSL) is rapidly closing the gap with supervised methods on large computer vision benchmarks. A successful approach to SSL is to learn embeddings which are…