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Dynamics of Deep Neural Networks and Neural Tangent Hierarchy

Dynamics of Deep Neural Networks and Neural Tangent Hierarchy

18 September 2019
Jiaoyang Huang
H. Yau
ArXivPDFHTML

Papers citing "Dynamics of Deep Neural Networks and Neural Tangent Hierarchy"

43 / 43 papers shown
Title
Information-theoretic reduction of deep neural networks to linear models in the overparametrized proportional regime
Information-theoretic reduction of deep neural networks to linear models in the overparametrized proportional regime
Francesco Camilli
D. Tieplova
Eleonora Bergamin
Jean Barbier
189
0
0
06 May 2025
Equivariant Neural Tangent Kernels
Equivariant Neural Tangent Kernels
Philipp Misof
Pan Kessel
Jan E. Gerken
64
0
0
10 Jun 2024
A Theory of Non-Linear Feature Learning with One Gradient Step in Two-Layer Neural Networks
A Theory of Non-Linear Feature Learning with One Gradient Step in Two-Layer Neural Networks
Behrad Moniri
Donghwan Lee
Hamed Hassani
Yan Sun
MLT
45
19
0
11 Oct 2023
Dynamics of Finite Width Kernel and Prediction Fluctuations in Mean
  Field Neural Networks
Dynamics of Finite Width Kernel and Prediction Fluctuations in Mean Field Neural Networks
Blake Bordelon
Cengiz Pehlevan
MLT
40
29
0
06 Apr 2023
Wide neural networks: From non-gaussian random fields at initialization
  to the NTK geometry of training
Wide neural networks: From non-gaussian random fields at initialization to the NTK geometry of training
Luís Carvalho
Joao L. Costa
José Mourao
Gonccalo Oliveira
AI4CE
26
1
0
06 Apr 2023
Controlled Descent Training
Controlled Descent Training
Viktor Andersson
B. Varga
Vincent Szolnoky
Andreas Syrén
Rebecka Jörnsten
Balázs Kulcsár
43
1
0
16 Mar 2023
Phase Diagram of Initial Condensation for Two-layer Neural Networks
Phase Diagram of Initial Condensation for Two-layer Neural Networks
Zheng Chen
Yuqing Li
Tao Luo
Zhaoguang Zhou
Z. Xu
MLT
AI4CE
49
9
0
12 Mar 2023
Efficient Parametric Approximations of Neural Network Function Space
  Distance
Efficient Parametric Approximations of Neural Network Function Space Distance
Nikita Dhawan
Sicong Huang
Juhan Bae
Roger C. Grosse
16
5
0
07 Feb 2023
Over-parameterised Shallow Neural Networks with Asymmetrical Node Scaling: Global Convergence Guarantees and Feature Learning
Over-parameterised Shallow Neural Networks with Asymmetrical Node Scaling: Global Convergence Guarantees and Feature Learning
François Caron
Fadhel Ayed
Paul Jung
Hoileong Lee
Juho Lee
Hongseok Yang
67
2
0
02 Feb 2023
Catapult Dynamics and Phase Transitions in Quadratic Nets
Catapult Dynamics and Phase Transitions in Quadratic Nets
David Meltzer
Junyu Liu
29
9
0
18 Jan 2023
Evolution of Neural Tangent Kernels under Benign and Adversarial
  Training
Evolution of Neural Tangent Kernels under Benign and Adversarial Training
Noel Loo
Ramin Hasani
Alexander Amini
Daniela Rus
AAML
38
13
0
21 Oct 2022
Global Convergence of SGD On Two Layer Neural Nets
Global Convergence of SGD On Two Layer Neural Nets
Pulkit Gopalani
Anirbit Mukherjee
26
5
0
20 Oct 2022
Meta-Principled Family of Hyperparameter Scaling Strategies
Meta-Principled Family of Hyperparameter Scaling Strategies
Sho Yaida
58
16
0
10 Oct 2022
Second-order regression models exhibit progressive sharpening to the
  edge of stability
Second-order regression models exhibit progressive sharpening to the edge of stability
Atish Agarwala
Fabian Pedregosa
Jeffrey Pennington
37
26
0
10 Oct 2022
Neural Networks can Learn Representations with Gradient Descent
Neural Networks can Learn Representations with Gradient Descent
Alexandru Damian
Jason D. Lee
Mahdi Soltanolkotabi
SSL
MLT
25
114
0
30 Jun 2022
Bounding the Width of Neural Networks via Coupled Initialization -- A
  Worst Case Analysis
Bounding the Width of Neural Networks via Coupled Initialization -- A Worst Case Analysis
Alexander Munteanu
Simon Omlor
Zhao Song
David P. Woodruff
33
15
0
26 Jun 2022
Identifying good directions to escape the NTK regime and efficiently
  learn low-degree plus sparse polynomials
Identifying good directions to escape the NTK regime and efficiently learn low-degree plus sparse polynomials
Eshaan Nichani
Yunzhi Bai
Jason D. Lee
29
10
0
08 Jun 2022
Self-Consistent Dynamical Field Theory of Kernel Evolution in Wide
  Neural Networks
Self-Consistent Dynamical Field Theory of Kernel Evolution in Wide Neural Networks
Blake Bordelon
Cengiz Pehlevan
MLT
40
77
0
19 May 2022
High-dimensional Asymptotics of Feature Learning: How One Gradient Step
  Improves the Representation
High-dimensional Asymptotics of Feature Learning: How One Gradient Step Improves the Representation
Jimmy Ba
Murat A. Erdogdu
Taiji Suzuki
Zhichao Wang
Denny Wu
Greg Yang
MLT
42
121
0
03 May 2022
On Feature Learning in Neural Networks with Global Convergence
  Guarantees
On Feature Learning in Neural Networks with Global Convergence Guarantees
Zhengdao Chen
Eric Vanden-Eijnden
Joan Bruna
MLT
36
13
0
22 Apr 2022
Implicit Bias of MSE Gradient Optimization in Underparameterized Neural
  Networks
Implicit Bias of MSE Gradient Optimization in Underparameterized Neural Networks
Benjamin Bowman
Guido Montúfar
28
11
0
12 Jan 2022
Separation of Scales and a Thermodynamic Description of Feature Learning
  in Some CNNs
Separation of Scales and a Thermodynamic Description of Feature Learning in Some CNNs
Inbar Seroussi
Gadi Naveh
Zohar Ringel
37
51
0
31 Dec 2021
AIR-Net: Adaptive and Implicit Regularization Neural Network for Matrix
  Completion
AIR-Net: Adaptive and Implicit Regularization Neural Network for Matrix Completion
Zhemin Li
Tao Sun
Hongxia Wang
Bao Wang
50
6
0
12 Oct 2021
Dataset Distillation with Infinitely Wide Convolutional Networks
Dataset Distillation with Infinitely Wide Convolutional Networks
Timothy Nguyen
Roman Novak
Lechao Xiao
Jaehoon Lee
DD
51
231
0
27 Jul 2021
Convergence of Deep ReLU Networks
Convergence of Deep ReLU Networks
Yuesheng Xu
Haizhang Zhang
37
27
0
27 Jul 2021
Random Neural Networks in the Infinite Width Limit as Gaussian Processes
Random Neural Networks in the Infinite Width Limit as Gaussian Processes
Boris Hanin
BDL
32
44
0
04 Jul 2021
FL-NTK: A Neural Tangent Kernel-based Framework for Federated Learning
  Convergence Analysis
FL-NTK: A Neural Tangent Kernel-based Framework for Federated Learning Convergence Analysis
Baihe Huang
Xiaoxiao Li
Zhao Song
Xin Yang
FedML
31
16
0
11 May 2021
On the Proof of Global Convergence of Gradient Descent for Deep ReLU
  Networks with Linear Widths
On the Proof of Global Convergence of Gradient Descent for Deep ReLU Networks with Linear Widths
Quynh N. Nguyen
53
48
0
24 Jan 2021
A Convergence Theory Towards Practical Over-parameterized Deep Neural
  Networks
A Convergence Theory Towards Practical Over-parameterized Deep Neural Networks
Asaf Noy
Yi Tian Xu
Y. Aflalo
Lihi Zelnik-Manor
Rong Jin
41
3
0
12 Jan 2021
Tight Bounds on the Smallest Eigenvalue of the Neural Tangent Kernel for
  Deep ReLU Networks
Tight Bounds on the Smallest Eigenvalue of the Neural Tangent Kernel for Deep ReLU Networks
Quynh N. Nguyen
Marco Mondelli
Guido Montúfar
25
81
0
21 Dec 2020
Gradient Starvation: A Learning Proclivity in Neural Networks
Gradient Starvation: A Learning Proclivity in Neural Networks
Mohammad Pezeshki
Sekouba Kaba
Yoshua Bengio
Aaron Courville
Doina Precup
Guillaume Lajoie
MLT
52
258
0
18 Nov 2020
Deep Networks and the Multiple Manifold Problem
Deep Networks and the Multiple Manifold Problem
Sam Buchanan
D. Gilboa
John N. Wright
166
39
0
25 Aug 2020
Whitening and second order optimization both make information in the
  dataset unusable during training, and can reduce or prevent generalization
Whitening and second order optimization both make information in the dataset unusable during training, and can reduce or prevent generalization
Neha S. Wadia
Daniel Duckworth
S. Schoenholz
Ethan Dyer
Jascha Narain Sohl-Dickstein
29
13
0
17 Aug 2020
Tensor Programs II: Neural Tangent Kernel for Any Architecture
Tensor Programs II: Neural Tangent Kernel for Any Architecture
Greg Yang
58
135
0
25 Jun 2020
Spectra of the Conjugate Kernel and Neural Tangent Kernel for
  linear-width neural networks
Spectra of the Conjugate Kernel and Neural Tangent Kernel for linear-width neural networks
Z. Fan
Zhichao Wang
44
71
0
25 May 2020
Provable Training of a ReLU Gate with an Iterative Non-Gradient
  Algorithm
Provable Training of a ReLU Gate with an Iterative Non-Gradient Algorithm
Sayar Karmakar
Anirbit Mukherjee
14
7
0
08 May 2020
Predicting the outputs of finite deep neural networks trained with noisy
  gradients
Predicting the outputs of finite deep neural networks trained with noisy gradients
Gadi Naveh
Oded Ben-David
H. Sompolinsky
Zohar Ringel
19
21
0
02 Apr 2020
Frequency Bias in Neural Networks for Input of Non-Uniform Density
Frequency Bias in Neural Networks for Input of Non-Uniform Density
Ronen Basri
Meirav Galun
Amnon Geifman
David Jacobs
Yoni Kasten
S. Kritchman
45
183
0
10 Mar 2020
The large learning rate phase of deep learning: the catapult mechanism
The large learning rate phase of deep learning: the catapult mechanism
Aitor Lewkowycz
Yasaman Bahri
Ethan Dyer
Jascha Narain Sohl-Dickstein
Guy Gur-Ari
ODL
159
235
0
04 Mar 2020
Neural Spectrum Alignment: Empirical Study
Neural Spectrum Alignment: Empirical Study
Dmitry Kopitkov
Vadim Indelman
35
14
0
19 Oct 2019
Asymptotics of Wide Networks from Feynman Diagrams
Asymptotics of Wide Networks from Feynman Diagrams
Ethan Dyer
Guy Gur-Ari
32
113
0
25 Sep 2019
Google's Neural Machine Translation System: Bridging the Gap between
  Human and Machine Translation
Google's Neural Machine Translation System: Bridging the Gap between Human and Machine Translation
Yonghui Wu
M. Schuster
Zhehuai Chen
Quoc V. Le
Mohammad Norouzi
...
Alex Rudnick
Oriol Vinyals
G. Corrado
Macduff Hughes
J. Dean
AIMat
718
6,748
0
26 Sep 2016
The Loss Surfaces of Multilayer Networks
The Loss Surfaces of Multilayer Networks
A. Choromańska
Mikael Henaff
Michaël Mathieu
Gerard Ben Arous
Yann LeCun
ODL
186
1,186
0
30 Nov 2014
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