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What Jian Sun thinks about neural networks

@jian-sun · 4 positions · 0 changes of mind

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 ↗

Jian Sun did not write this page.

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.

2 dated positions, 2015, in their own words. Our reading of what Jian Sun has said — not written or endorsed by them.

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  1. Our readingDepth is not free: past a point, deeper neural networks are harder to train rather than simply better.

    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

  3. Our readingResidual networks are easier to optimize than plain ones and keep gaining accuracy as depth increases.

    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