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Towards a General Theory of Infinite-Width Limits of Neural Classifiers

Towards a General Theory of Infinite-Width Limits of Neural Classifiers

12 March 2020
Eugene Golikov
    AI4CE
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Papers citing "Towards a General Theory of Infinite-Width Limits of Neural Classifiers"

3 / 3 papers shown
Title
Infinite-width limit of deep linear neural networks
Infinite-width limit of deep linear neural networks
Lénaïc Chizat
Maria Colombo
Xavier Fernández-Real
Alessio Figalli
31
14
0
29 Nov 2022
The Limitations of Large Width in Neural Networks: A Deep Gaussian
  Process Perspective
The Limitations of Large Width in Neural Networks: A Deep Gaussian Process Perspective
Geoff Pleiss
John P. Cunningham
28
24
0
11 Jun 2021
Dynamical Isometry and a Mean Field Theory of CNNs: How to Train
  10,000-Layer Vanilla Convolutional Neural Networks
Dynamical Isometry and a Mean Field Theory of CNNs: How to Train 10,000-Layer Vanilla Convolutional Neural Networks
Lechao Xiao
Yasaman Bahri
Jascha Narain Sohl-Dickstein
S. Schoenholz
Jeffrey Pennington
233
348
0
14 Jun 2018
1