Jian Sun
Computer vision researcher, a co-author of residual networks. Led the visual computing group at Microsoft Research Asia and was chief scientist at Megvii. Died in 2022; this page reflects his complete public record.
Everything they publish, on ppll ↗
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We collected these quotes from things they published elsewhere, and every quote links to where it was said. They have no account here and have not endorsed this site. Quotes are word for word; the short line under each one is our own restatement, not their wording. Their own site. Is this you? Claim it or ask us to remove it. Or tell us what is wrong here.
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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 2nd 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 4th 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 6th 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 8th of 8 in this piece