Kaiming He
Associate professor at MIT and first author of the residual networks paper, the most cited paper in modern computer vision. Previously at Meta AI Research and Microsoft Research Asia.
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Their wordsDeeper neural networks are more difficult to train.
↗He, Zhang, Ren & Sun, "Deep Residual Learning for Image Recognition" (arXiv)arxiv.org 1st of 8 in this piece
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Their wordsWe explicitly reformulate the layers as learning residual functions with reference to the layer inputs, instead of learning unreferenced functions.
↗He, Zhang, Ren & Sun, "Deep Residual Learning for Image Recognition" (arXiv)arxiv.org 3rd of 8 in this piece
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Their wordsWe provide comprehensive empirical evidence showing that these residual networks are easier to optimize, and can gain accuracy from considerably increased depth.
↗He, Zhang, Ren & Sun, "Deep Residual Learning for Image Recognition" (arXiv)arxiv.org 5th of 8 in this piece
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Their wordsThe depth of representations is of central importance for many visual recognition tasks.
↗He, Zhang, Ren & Sun, "Deep Residual Learning for Image Recognition" (arXiv)arxiv.org 7th of 8 in this piece