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1902.02880
Cited By
Mean Field Limit of the Learning Dynamics of Multilayer Neural Networks
7 February 2019
Phan-Minh Nguyen
AI4CE
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Papers citing
"Mean Field Limit of the Learning Dynamics of Multilayer Neural Networks"
48 / 48 papers shown
Title
Mean-Field Analysis for Learning Subspace-Sparse Polynomials with Gaussian Input
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Rong Ge
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0
10 Jan 2025
A Mean Field Theory of Batch Normalization
Greg Yang
Jeffrey Pennington
Vinay Rao
Jascha Narain Sohl-Dickstein
S. Schoenholz
72
179
0
21 Feb 2019
Scaling description of generalization with number of parameters in deep learning
Mario Geiger
Arthur Jacot
S. Spigler
Franck Gabriel
Levent Sagun
Stéphane dÁscoli
Giulio Biroli
Clément Hongler
Matthieu Wyart
83
196
0
06 Jan 2019
Analysis of a Two-Layer Neural Network via Displacement Convexity
Adel Javanmard
Marco Mondelli
Andrea Montanari
MLT
87
57
0
05 Jan 2019
On Lazy Training in Differentiable Programming
Lénaïc Chizat
Edouard Oyallon
Francis R. Bach
111
839
0
19 Dec 2018
Stochastic Gradient Descent Optimizes Over-parameterized Deep ReLU Networks
Difan Zou
Yuan Cao
Dongruo Zhou
Quanquan Gu
ODL
190
448
0
21 Nov 2018
Learning and Generalization in Overparameterized Neural Networks, Going Beyond Two Layers
Zeyuan Allen-Zhu
Yuanzhi Li
Yingyu Liang
MLT
201
773
0
12 Nov 2018
A Convergence Theory for Deep Learning via Over-Parameterization
Zeyuan Allen-Zhu
Yuanzhi Li
Zhao Song
AI4CE
ODL
264
1,466
0
09 Nov 2018
Gradient Descent Finds Global Minima of Deep Neural Networks
S. Du
Jason D. Lee
Haochuan Li
Liwei Wang
Masayoshi Tomizuka
ODL
211
1,135
0
09 Nov 2018
A jamming transition from under- to over-parametrization affects loss landscape and generalization
S. Spigler
Mario Geiger
Stéphane dÁscoli
Levent Sagun
Giulio Biroli
Matthieu Wyart
64
150
0
22 Oct 2018
Regularization Matters: Generalization and Optimization of Neural Nets v.s. their Induced Kernel
Colin Wei
Jason D. Lee
Qiang Liu
Tengyu Ma
214
245
0
12 Oct 2018
Bayesian Deep Convolutional Networks with Many Channels are Gaussian Processes
Roman Novak
Lechao Xiao
Jaehoon Lee
Yasaman Bahri
Greg Yang
Jiri Hron
Daniel A. Abolafia
Jeffrey Pennington
Jascha Narain Sohl-Dickstein
UQCV
BDL
68
310
0
11 Oct 2018
Gradient Descent Provably Optimizes Over-parameterized Neural Networks
S. Du
Xiyu Zhai
Barnabás Póczós
Aarti Singh
MLT
ODL
227
1,275
0
04 Oct 2018
The jamming transition as a paradigm to understand the loss landscape of deep neural networks
Mario Geiger
S. Spigler
Stéphane dÁscoli
Levent Sagun
Marco Baity-Jesi
Giulio Biroli
Matthieu Wyart
51
143
0
25 Sep 2018
Mean Field Analysis of Neural Networks: A Central Limit Theorem
Justin A. Sirignano
K. Spiliopoulos
MLT
75
194
0
28 Aug 2018
Deep Convolutional Networks as shallow Gaussian Processes
Adrià Garriga-Alonso
C. Rasmussen
Laurence Aitchison
BDL
UQCV
109
271
0
16 Aug 2018
Learning Overparameterized Neural Networks via Stochastic Gradient Descent on Structured Data
Yuanzhi Li
Yingyu Liang
MLT
219
653
0
03 Aug 2018
Neural Tangent Kernel: Convergence and Generalization in Neural Networks
Arthur Jacot
Franck Gabriel
Clément Hongler
271
3,213
0
20 Jun 2018
Dynamical Isometry and a Mean Field Theory of RNNs: Gating Enables Signal Propagation in Recurrent Neural Networks
Minmin Chen
Jeffrey Pennington
S. Schoenholz
SyDa
AI4CE
57
116
0
14 Jun 2018
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
304
354
0
14 Jun 2018
On the Global Convergence of Gradient Descent for Over-parameterized Models using Optimal Transport
Lénaïc Chizat
Francis R. Bach
OT
212
736
0
24 May 2018
Gaussian Process Behaviour in Wide Deep Neural Networks
A. G. Matthews
Mark Rowland
Jiri Hron
Richard Turner
Zoubin Ghahramani
BDL
152
559
0
30 Apr 2018
The loss landscape of overparameterized neural networks
Y. Cooper
49
77
0
26 Apr 2018
A Mean Field View of the Landscape of Two-Layers Neural Networks
Song Mei
Andrea Montanari
Phan-Minh Nguyen
MLT
101
861
0
18 Apr 2018
How to Start Training: The Effect of Initialization and Architecture
Boris Hanin
David Rolnick
73
255
0
05 Mar 2018
On the Power of Over-parametrization in Neural Networks with Quadratic Activation
S. Du
Jason D. Lee
183
272
0
03 Mar 2018
Spurious Valleys in Two-layer Neural Network Optimization Landscapes
Luca Venturi
Afonso S. Bandeira
Joan Bruna
60
74
0
18 Feb 2018
Small nonlinearities in activation functions create bad local minima in neural networks
Chulhee Yun
S. Sra
Ali Jadbabaie
ODL
74
95
0
10 Feb 2018
Which Neural Net Architectures Give Rise To Exploding and Vanishing Gradients?
Boris Hanin
65
254
0
11 Jan 2018
Mean Field Residual Networks: On the Edge of Chaos
Greg Yang
S. Schoenholz
67
194
0
24 Dec 2017
Resurrecting the sigmoid in deep learning through dynamical isometry: theory and practice
Jeffrey Pennington
S. Schoenholz
Surya Ganguli
ODL
43
253
0
13 Nov 2017
Deep Neural Networks as Gaussian Processes
Jaehoon Lee
Yasaman Bahri
Roman Novak
S. Schoenholz
Jeffrey Pennington
Jascha Narain Sohl-Dickstein
UQCV
BDL
131
1,097
0
01 Nov 2017
Theoretical insights into the optimization landscape of over-parameterized shallow neural networks
Mahdi Soltanolkotabi
Adel Javanmard
Jason D. Lee
175
423
0
16 Jul 2017
Recovery Guarantees for One-hidden-layer Neural Networks
Kai Zhong
Zhao Song
Prateek Jain
Peter L. Bartlett
Inderjit S. Dhillon
MLT
175
337
0
10 Jun 2017
The loss surface of deep and wide neural networks
Quynh N. Nguyen
Matthias Hein
ODL
164
285
0
26 Apr 2017
Opening the Black Box of Deep Neural Networks via Information
Ravid Shwartz-Ziv
Naftali Tishby
AI4CE
105
1,416
0
02 Mar 2017
Topology and Geometry of Half-Rectified Network Optimization
C. Freeman
Joan Bruna
218
235
0
04 Nov 2016
Deep vs. shallow networks : An approximation theory perspective
H. Mhaskar
T. Poggio
165
341
0
10 Aug 2016
The Landscape of Empirical Risk for Non-convex Losses
Song Mei
Yu Bai
Andrea Montanari
117
313
0
22 Jul 2016
Exponential expressivity in deep neural networks through transient chaos
Ben Poole
Subhaneil Lahiri
M. Raghu
Jascha Narain Sohl-Dickstein
Surya Ganguli
90
595
0
16 Jun 2016
No bad local minima: Data independent training error guarantees for multilayer neural networks
Daniel Soudry
Y. Carmon
188
235
0
26 May 2016
Understanding Deep Convolutional Networks
S. Mallat
FAtt
AI4CE
175
641
0
19 Jan 2016
On the Quality of the Initial Basin in Overspecified Neural Networks
Itay Safran
Ohad Shamir
78
127
0
13 Nov 2015
Steps Toward Deep Kernel Methods from Infinite Neural Networks
Tamir Hazan
Tommi Jaakkola
80
83
0
20 Aug 2015
The Loss Surfaces of Multilayer Networks
A. Choromańska
Mikael Henaff
Michaël Mathieu
Gerard Ben Arous
Yann LeCun
ODL
261
1,200
0
30 Nov 2014
Very Deep Convolutional Networks for Large-Scale Image Recognition
Karen Simonyan
Andrew Zisserman
FAtt
MDE
1.7K
100,479
0
04 Sep 2014
ImageNet Large Scale Visual Recognition Challenge
Olga Russakovsky
Jia Deng
Hao Su
J. Krause
S. Satheesh
...
A. Karpathy
A. Khosla
Michael S. Bernstein
Alexander C. Berg
Li Fei-Fei
VLM
ObjD
1.7K
39,590
0
01 Sep 2014
Provable Bounds for Learning Some Deep Representations
Sanjeev Arora
Aditya Bhaskara
Rong Ge
Tengyu Ma
BDL
97
335
0
23 Oct 2013
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