#09 – Automatic Differentiation in Machine Learning: a Survey
Misreading Chat · Hajime Morrita
May 17, 201841m 28s
Audio is streamed directly from the publisher (misreadingchat.files.wordpress.com) as published in their RSS feed. Play Podcasts does not host this file. Rights-holders can request removal through the copyright & takedown page.
Show Notes
自動微分のサーベイ論文 “Automatic differentiation in machine learning: a survey” を 森田が PyTorch のコードを読みつつ紹介します。
- [1502.05767] Automatic differentiation in machine learning: a survey
- Automatic differentiation in PyTorch | OpenReview
- Chainer: a next-generation open source framework for deep learning
- Implementation of Control Flow in TensorFlow
- pytorch/pytorch: Tensors and Dynamic neural networks in Python with strong GPU acceleration
- Release alpha-1 release · pytorch/pytorch aka. v0.1.1
- Yann LeCun on Twitter: “Dude, there were graph-based deep learning frameworks with AD back in 1991 (SN at AT&T) and its open source successor Lush, released in 2002.… https://t.co/sL2wPnaOJY”
- 深層学習 (Goodfellow の教科書日本語訳)
Follow-up and Correction
- Netflix Research
- How to Adopt Modern C++17 into Your C++ Code – YouTube
- Carnegie Mellon Launches Undergraduate Degree in Artificial Intelligence | Carnegie Mellon School of Computer Science
- PyTorch の論文は 2017 の Autodiff Workshop で発表されていたようです。
- 10:25 あたりで計算途中の変数が Tensor になっていると言っていますが、Variable の間違いです。