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文件名称：CS294-158 课件PDF.rar
文件大小：84.08MB
文件格式：RAR
更新时间：2022-07-03 02:45:58
CS294
本课程要求具有 CS 189 或同等学力。本课程将假定你已了解强化学习、数值优化和机器学习的相关背景知识。
【文件预览】：
CS294-158 课件PDF
----Lecture 1a Logistics.pdf(477KB)
----Lecture 1b - Motivation.pdf(5.96MB)
----Lecture 4a - Latent Variable Models - part 2.pdf(3.56MB)
----Lecture 9a - Unsupervised Distribution Alignment.pdf(4.17MB)
----Lecture 8b - Semi-Supervised Learning_ A quick primer.pdf(2.25MB)
----Lecture 2c+3a - Flow Models.pdf(2.84MB)
----Lecture 6b+7 - Non-Generative Representation Learning.pdf(13.34MB)
----Lecture 5c+6a - Implicit Models (GANs).pdf(40.56MB)
----Lecture 2b - Lossless Compression.pdf(10.88MB)
----Lecture 8a - Round-up of Strengths and Weaknesses.pdf(5.68MB)
----Lecture 4b - Bits-Back Coding.pdf(8.83MB)
----Lecture 10 - Representation Learning in Reinforcement Learning.pdf(9.71MB)
----Lecture 3b - Latent Variable Models - part 1.pdf(2.2MB)
----Lecture 1c+2a - Autoregressive Models.pdf(5.28MB)