“深度学习理论、算法与应用”研讨会视频集锦

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2017-10-20 20:32:59
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11
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https://www.youtube.com/playlist?list=PLJOzdkh8T5kqCNV_v1w2tapvtJDZYiohW “Deep Learning: Theory, Algorithms, and Applications”
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视频选集
(1/18)
01. It is time for a theory of deep learning
01:05:03
02. Learning in the Machine
43:38
03. Hunting for Cosmic Rays with Smartphones and Deep Learning
29:39
04. Optimal Approximation with Sparsely Connected DNNs
34:17
05. Learning to make reward-guided decisions
26:53
06. Explaining Decisions of Neural Networks by LRP
20:41
07. Learning 3D Vision
37:21
08. What can we learn from interpreting deep neural networks
41:58
09. Regularized Wasserstein Distances & Minimum Kantorovich Estimators
32:31
10. Emergence of Invariance and Disentangling in Deep Representations
26:52
11. Deep Neural Networks - A Bayesian Perspective
27:47
12. Deep Taylor decomposition
23:11
13. Learning from weak supervision
36:21
14. Neural Combinatorial Optimization with Reinforcement Learning
33:22
15. Local minima and saddle points in hierarchical structure of neural
31:11
16. Deep Learning meets quantum chemistry
01:01:58
17. Self-normalizing Neural Networks and a Two Time-Scale Update Rule for GANs
41:35
18. Information Theory of Deep Learning
57:54
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