Communities
Connect sessions
AI calendar
Organizations
Join Slack
Contact Sales
Search
Open menu
Home
Papers
1806.07572
Cited By
v1
v2
v3
v4 (latest)
Neural Tangent Kernel: Convergence and Generalization in Neural Networks
20 June 2018
Arthur Jacot
Franck Gabriel
Clément Hongler
Re-assign community
ArXiv (abs)
PDF
HTML
Papers citing
"Neural Tangent Kernel: Convergence and Generalization in Neural Networks"
50 / 2,413 papers shown
Disentangling Trainability and Generalization in Deep Neural Networks
Lechao Xiao
Jeffrey Pennington
S. Schoenholz
199
34
0
30 Dec 2019
Deep Graph Similarity Learning: A Survey
Data mining and knowledge discovery (DMKD), 2019
Guixiang Ma
Nesreen Ahmed
Theodore L. Willke
Philip S. Yu
GNN
239
90
0
25 Dec 2019
Landscape Connectivity and Dropout Stability of SGD Solutions for Over-parameterized Neural Networks
International Conference on Machine Learning (ICML), 2019
Aleksandr Shevchenko
Marco Mondelli
433
41
0
20 Dec 2019
Optimization for deep learning: theory and algorithms
Tian Ding
ODL
343
178
0
19 Dec 2019
Analytic expressions for the output evolution of a deep neural network
Anastasia Borovykh
112
0
0
18 Dec 2019
Frivolous Units: Wider Networks Are Not Really That Wide
AAAI Conference on Artificial Intelligence (AAAI), 2019
Stephen Casper
Xavier Boix
Vanessa D’Amario
Ling Guo
Martin Schrimpf
Kasper Vinken
Gabriel Kreiman
257
20
0
10 Dec 2019
A Finite-Time Analysis of Q-Learning with Neural Network Function Approximation
International Conference on Machine Learning (ICML), 2019
Pan Xu
Quanquan Gu
229
77
0
10 Dec 2019
A priori generalization error for two-layer ReLU neural network through minimum norm solution
Zhi-Qin John Xu
Jiwei Zhang
Yaoyu Zhang
Chengchao Zhao
MLT
184
1
0
06 Dec 2019
Observational Overfitting in Reinforcement Learning
International Conference on Learning Representations (ICLR), 2019
Xingyou Song
Yiding Jiang
Stephen Tu
Yilun Du
Behnam Neyshabur
OffRL
275
147
0
06 Dec 2019
Neural Tangents: Fast and Easy Infinite Neural Networks in Python
International Conference on Learning Representations (ICLR), 2019
Roman Novak
Lechao Xiao
Jiri Hron
Jaehoon Lee
Alexander A. Alemi
Jascha Narain Sohl-Dickstein
S. Schoenholz
247
249
0
05 Dec 2019
Towards Understanding the Spectral Bias of Deep Learning
International Joint Conference on Artificial Intelligence (IJCAI), 2019
Yuan Cao
Zhiying Fang
Yue Wu
Ding-Xuan Zhou
Quanquan Gu
474
268
0
03 Dec 2019
Variable Selection with Rigorous Uncertainty Quantification using Deep Bayesian Neural Networks: Posterior Concentration and Bernstein-von Mises Phenomenon
International Conference on Artificial Intelligence and Statistics (AISTATS), 2019
Jeremiah Zhe Liu
BDL
290
10
0
03 Dec 2019
A Random Matrix Perspective on Mixtures of Nonlinearities for Deep Learning
International Conference on Artificial Intelligence and Statistics (AISTATS), 2019
Ben Adlam
J. Levinson
Jeffrey Pennington
184
26
0
02 Dec 2019
On the optimality of kernels for high-dimensional clustering
International Conference on Artificial Intelligence and Statistics (AISTATS), 2019
L. C. Vankadara
Debarghya Ghoshdastidar
212
14
0
01 Dec 2019
On the Heavy-Tailed Theory of Stochastic Gradient Descent for Deep Neural Networks
Umut Simsekli
Mert Gurbuzbalaban
T. H. Nguyen
G. Richard
Levent Sagun
323
64
0
29 Nov 2019
How Much Over-parameterization Is Sufficient to Learn Deep ReLU Networks?
International Conference on Learning Representations (ICLR), 2019
Zixiang Chen
Yuan Cao
Difan Zou
Quanquan Gu
330
129
0
27 Nov 2019
Benefits of Jointly Training Autoencoders: An Improved Neural Tangent Kernel Analysis
IEEE Transactions on Information Theory (IEEE Trans. Inf. Theory), 2019
THANH VAN NGUYEN
Raymond K. W. Wong
Chinmay Hegde
269
14
0
27 Nov 2019
Gating Revisited: Deep Multi-layer RNNs That Can Be Trained
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2019
Mehmet Özgür Türkoglu
Stefano Dáronco
Jan Dirk Wegner
Konrad Schindler
447
60
0
25 Nov 2019
Neural Networks Learning and Memorization with (almost) no Over-Parameterization
Neural Information Processing Systems (NeurIPS), 2019
Amit Daniely
166
36
0
22 Nov 2019
Information in Infinite Ensembles of Infinitely-Wide Neural Networks
Symposium on Advances in Approximate Bayesian Inference (AABI), 2019
Ravid Shwartz-Ziv
Alexander A. Alemi
247
22
0
20 Nov 2019
Implicit Regularization and Convergence for Weight Normalization
Neural Information Processing Systems (NeurIPS), 2019
Xiaoxia Wu
Guang Cheng
Zhaolin Ren
Shanshan Wu
Zhiyuan Li
Suriya Gunasekar
Rachel A. Ward
Qiang Liu
534
26
0
18 Nov 2019
Convex Formulation of Overparameterized Deep Neural Networks
IEEE Transactions on Information Theory (IEEE Trans. Inf. Theory), 2019
Cong Fang
Yihong Gu
Weizhong Zhang
Tong Zhang
130
28
0
18 Nov 2019
Asymptotics of Reinforcement Learning with Neural Networks
Justin A. Sirignano
K. Spiliopoulos
MLT
408
14
0
13 Nov 2019
Neural Contextual Bandits with UCB-based Exploration
Dongruo Zhou
Lihong Li
Quanquan Gu
427
16
0
11 Nov 2019
How Implicit Regularization of ReLU Neural Networks Characterizes the Learned Function -- Part I: the 1-D Case of Two Layers with Random First Layer
Jakob Heiss
Josef Teichmann
Hanna Wutte
MLT
230
5
0
07 Nov 2019
Sub-Optimal Local Minima Exist for Neural Networks with Almost All Non-Linear Activations
Tian Ding
Dawei Li
Tian Ding
343
14
0
04 Nov 2019
Mean-field inference methods for neural networks
Marylou Gabrié
AI4CE
376
37
0
03 Nov 2019
Enhanced Convolutional Neural Tangent Kernels
Zhiyuan Li
Ruosong Wang
Dingli Yu
S. Du
Wei Hu
Ruslan Salakhutdinov
Sanjeev Arora
198
136
0
03 Nov 2019
Gaussian-Spherical Restricted Boltzmann Machines
A. Decelle
Cyril Furtlehner
156
8
0
31 Oct 2019
Tensor Programs I: Wide Feedforward or Recurrent Neural Networks of Any Architecture are Gaussian Processes
Neural Information Processing Systems (NeurIPS), 2019
Greg Yang
491
221
0
28 Oct 2019
Learning Boolean Circuits with Neural Networks
Eran Malach
Shai Shalev-Shwartz
178
4
0
25 Oct 2019
Multi-scale Deep Neural Networks for Solving High Dimensional PDEs
Wei Cai
Zhi-Qin John Xu
AI4CE
235
50
0
25 Oct 2019
Over Parameterized Two-level Neural Networks Can Learn Near Optimal Feature Representations
Cong Fang
Hanze Dong
Tong Zhang
135
18
0
25 Oct 2019
Neural Spectrum Alignment: Empirical Study
International Conference on Artificial Neural Networks (ICANN), 2019
Dmitry Kopitkov
Vadim Indelman
211
14
0
19 Oct 2019
Why bigger is not always better: on finite and infinite neural networks
International Conference on Machine Learning (ICML), 2019
Laurence Aitchison
434
58
0
17 Oct 2019
The Renyi Gaussian Process: Towards Improved Generalization
IISE Transactions (IISE Trans.), 2019
Xubo Yue
Raed Al Kontar
377
3
0
15 Oct 2019
Neural tangent kernels, transportation mappings, and universal approximation
International Conference on Learning Representations (ICLR), 2019
Ziwei Ji
Matus Telgarsky
Ruicheng Xian
131
44
0
15 Oct 2019
Pathological spectra of the Fisher information metric and its variants in deep neural networks
Neural Computation (Neural Comput.), 2019
Ryo Karakida
S. Akaho
S. Amari
211
34
0
14 Oct 2019
Emergent properties of the local geometry of neural loss landscapes
Stanislav Fort
Surya Ganguli
225
55
0
14 Oct 2019
Large Deviation Analysis of Function Sensitivity in Random Deep Neural Networks
Bo Li
D. Saad
136
12
0
13 Oct 2019
On the expected behaviour of noise regularised deep neural networks as Gaussian processes
Pattern Recognition Letters (PR), 2019
Arnu Pretorius
Herman Kamper
Steve Kroon
187
9
0
12 Oct 2019
Harnessing the Power of Infinitely Wide Deep Nets on Small-data Tasks
International Conference on Learning Representations (ICLR), 2019
Sanjeev Arora
S. Du
Zhiyuan Li
Ruslan Salakhutdinov
Ruosong Wang
Dingli Yu
AAML
265
166
0
03 Oct 2019
Beyond Linearization: On Quadratic and Higher-Order Approximation of Wide Neural Networks
International Conference on Learning Representations (ICLR), 2019
Yu Bai
Jason D. Lee
194
125
0
03 Oct 2019
Distillation
≈
\approx
≈
Early Stopping? Harvesting Dark Knowledge Utilizing Anisotropic Information Retrieval For Overparameterized Neural Network
Bin Dong
Jikai Hou
Yiping Lu
Zhihua Zhang
170
43
0
02 Oct 2019
Truth or Backpropaganda? An Empirical Investigation of Deep Learning Theory
International Conference on Learning Representations (ICLR), 2019
Micah Goldblum
Jonas Geiping
Avi Schwarzschild
Michael Moeller
Tom Goldstein
476
36
0
01 Oct 2019
The asymptotic spectrum of the Hessian of DNN throughout training
International Conference on Learning Representations (ICLR), 2019
Arthur Jacot
Franck Gabriel
Clément Hongler
301
38
0
01 Oct 2019
Non-Gaussian processes and neural networks at finite widths
Mathematical and Scientific Machine Learning (MSML), 2019
Sho Yaida
325
99
0
30 Sep 2019
Student Specialization in Deep ReLU Networks With Finite Width and Input Dimension
Yuandong Tian
MLT
218
8
0
30 Sep 2019
Overparameterized Neural Networks Implement Associative Memory
Proceedings of the National Academy of Sciences of the United States of America (PNAS), 2019
Adityanarayanan Radhakrishnan
M. Belkin
Caroline Uhler
BDL
229
79
0
26 Sep 2019
Polylogarithmic width suffices for gradient descent to achieve arbitrarily small test error with shallow ReLU networks
International Conference on Learning Representations (ICLR), 2019
Ziwei Ji
Matus Telgarsky
261
188
0
26 Sep 2019
Previous
1
2
3
...
45
46
47
48
49
Next
Page 46 of 49
Page
of 49
Go
