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While matrix derivatives are important, there is also a lot of other math in DL papers. In particular, a lot of the probability side concerns expectations, KL d
by blt 9y ago
While matrix derivatives are important, there is also a lot of other math in DL papers. In particular, a lot of the probability side concerns expectations, KL divergences, entropy, etc., which are all defined in terms of integrals or sums. You need undergraduate-level probability background.
- jph00 9y agoThe first 5 chapters of the Goodfellow deep learning book are a great resource for understanding the probability, linear algebra, optimization, and information theory you need to digest deep learning papers.