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Intro
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Classroom Contents
Computation in Very Wide Neural Networks
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- 1 Intro
- 2 Outline
- 3 Starting point
- 4 Single-hidden layer (shallow) neural networks of infinite width Consider a NN which
- 5 What GP does it correspond to?
- 6 Properties of the NNGP
- 7 Bayesian inference with a GP prior (Review)
- 8 Experiments from original work
- 9 Performance comparison
- 10 NNGP performance across hyperparameters
- 11 Large depth behavior & fixed points
- 12 Phase diagrams: experiments vs. theory
- 13 Performance trends with width and dataset size
- 14 Empirical comparison of various NN-GPS
- 15 Empirical trends
- 16 Best performing networks: comparison between GPs and SGD-NNS
- 17 Partway summary
- 18 What dynamics occurs in parameter space?
- 19 Closing Remarks
