From Gaussian Process to Neural Tangent Kernel - 介紹無限寬的神經網路相關演算法 скачать в хорошем качестве

From Gaussian Process to Neural Tangent Kernel - 介紹無限寬的神經網路相關演算法

無限寬的神經網路演算法 - NNGP 及NTK介紹 0:00 From Gaussian Process to Neural Tangent Kernel 0:19 大綱 1:20 高斯過程 4:05 高斯過程回歸(GPR) 13:16 GPR範例 16:09 GPR with Kernel 17:22 隨機初始化深度學習網路=高斯過程(NNGP演算法) 18:16 單層神經網路 23:29 Arc-Cos Kernel 31:02 多層神經網路 34:10 Bayesian Inference with Gaussian Process and NNGP Numerical Algorithm 42:14 NNGP 實驗 47:35 Neural Tangent Kernel(NTK) 48:54 Dual Space and Bilinear Form 52:24 網路初始化時的NTK 1:08:43 訓練網路時的NTK 1:22:00 更多種類的NTK 1:26:38 Neural Tangent 套件：介紹如何用套件客製化NNGP及NTK網路 reference: https://github.com/google/neural-tang... https://github.com/brain-research/nngp A. Jacot et al. 2018, Neural Tangent Kernel: Convergence and Generalization in Neural Networks S. Arora et al. 2019, On Exact Computation with an Infinitely Wide Neural Net R. Navok et al. 2019, Neural Tangents: Fast and Easy Infinite Neural Networks in Python J. Lee et al. 2018, Deep Neural Networks as Gaussian Process Z. Li et al. 2019, Enhanced Convolutional Neural Tangent Kernels Liu et al. 2019, When Gaussian Process Meets Big Data: A Review of Scalable GPs A. Rahimi et al. 2007, Random Features for Large-Scale Kernel Machines Y. Cho et al. 2009, Kernel Methods for Deep Learning J. Lee et al. 2019, Wide Neural Networks of Any Depth Evolves as Linear Models Under Gradient Descent J. Hron et al. 2020, Infinite Attention: NNGP an d NTK for Deep Attention Networks A. G Matthews et al. 2018, Gaussian Process Behavior in Wide Deep Neural Networks T. Beckers 2020, An introduction to Gaussian Process Models U.H. Gerlach 2016, The Dual of a Vector Space: From the Concrete to the Abstract to the Concrete https://www.maths.tcd.ie/~pete/ma1212... https://www.cs.princeton.edu/courses/... https://rajatvd.github.io/NTK/