Communities
Connect sessions
AI calendar
Organizations
Join Slack
Contact Sales
Search
Open menu
Home
Papers
2005.11879
Cited By
v1
v2
v3 (latest)
Spectra of the Conjugate Kernel and Neural Tangent Kernel for linear-width neural networks
25 May 2020
Z. Fan
Zhichao Wang
Re-assign community
ArXiv (abs)
PDF
HTML
Papers citing
"Spectra of the Conjugate Kernel and Neural Tangent Kernel for linear-width neural networks"
50 / 67 papers shown
Gaussian Equivalence for Self-Attention: Asymptotic Spectral Analysis of Attention Matrix
Tomohiro Hayase
B. Collins
Ryo Karakida
MLT
MILM
205
0
0
08 Oct 2025
Kernel ridge regression under power-law data: spectrum and generalization
Arie Wortsman
Bruno Loureiro
225
3
0
06 Oct 2025
Low Rank Gradients and Where to Find Them
Rishi Sonthalia
Michael Murray
Guido Montúfar
220
3
0
01 Oct 2025
Eigenvalue distribution of the Neural Tangent Kernel in the quadratic scaling
Lucas Benigni
Elliot Paquette
175
3
0
27 Aug 2025
Thompson Sampling in Function Spaces via Neural Operators
Rafael Oliveira
Xuesong Wang
Kian Ming A. Chai
Edwin Bonilla
294
0
0
27 Jun 2025
Understanding Overadaptation in Supervised Fine-Tuning: The Role of Ensemble Methods
Yifan Hao
Xingyuan Pan
Hanning Zhang
Chenlu Ye
Boyao Wang
Tong Zhang
342
2
0
02 Jun 2025
Free Random Projection for In-Context Reinforcement Learning
Tomohiro Hayase
B. Collins
Nakamasa Inoue
476
0
0
09 Apr 2025
What do physics-informed DeepONets learn? Understanding and improving training for scientific computing applications
Emily Williams
Amanda A. Howard
B. Meuris
P. Stinis
AI4CE
276
3
0
27 Nov 2024
A Random Matrix Theory Perspective on the Spectrum of Learned Features and Asymptotic Generalization Capabilities
International Conference on Artificial Intelligence and Statistics (AISTATS), 2024
Yatin Dandi
Luca Pesce
Hugo Cui
Florent Krzakala
Yue M. Lu
Bruno Loureiro
MLT
391
11
0
24 Oct 2024
Generalization for Least Squares Regression With Simple Spiked Covariances
Jiping Li
Rishi Sonthalia
298
1
0
17 Oct 2024
From Spikes to Heavy Tails: Unveiling the Spectral Evolution of Neural Networks
Vignesh Kothapalli
Tianyu Pang
Shenyang Deng
Zongmin Liu
Yaoqing Yang
464
4
0
07 Jun 2024
BWS: Best Window Selection Based on Sample Scores for Data Pruning across Broad Ranges
Hoyong Choi
Nohyun Ki
Hye Won Chung
293
9
0
05 Jun 2024
Bounds for the smallest eigenvalue of the NTK for arbitrary spherical data of arbitrary dimension
Neural Information Processing Systems (NeurIPS), 2024
Kedar Karhadkar
Michael Murray
Guido Montúfar
412
8
0
23 May 2024
The Positivity of the Neural Tangent Kernel
Luís Carvalho
Joao L. Costa
José Mourao
Gonccalo Oliveira
493
7
0
19 Apr 2024
Unifying Low Dimensional Observations in Deep Learning Through the Deep Linear Unconstrained Feature Model
Connall Garrod
Jonathan P. Keating
414
11
0
09 Apr 2024
"Lossless" Compression of Deep Neural Networks: A High-dimensional Neural Tangent Kernel Approach
Lingyu Gu
Yongqiang Du
Yuan Zhang
Di Xie
Shiliang Pu
Robert C. Qiu
Zhenyu Liao
266
9
0
01 Mar 2024
Asymptotics of Learning with Deep Structured (Random) Features
Dominik Schröder
Daniil Dmitriev
Hugo Cui
Bruno Loureiro
329
12
0
21 Feb 2024
Feature Mapping in Physics-Informed Neural Networks (PINNs)
Chengxi Zeng
T. Burghardt
A. Gambaruto
329
2
0
10 Feb 2024
Deep Equilibrium Models are Almost Equivalent to Not-so-deep Explicit Models for High-dimensional Gaussian Mixtures
Zenan Ling
Longbo Li
Zhanbo Feng
Yixuan Zhang
Feng Zhou
Robert C. Qiu
Zhenyu Liao
346
6
0
05 Feb 2024
Generalization in Kernel Regression Under Realistic Assumptions
Daniel Barzilai
Ohad Shamir
509
22
0
26 Dec 2023
Efficient kernel surrogates for neural network-based regression
S. Qadeer
A. Engel
Amanda A. Howard
Adam Tsou
Max Vargas
P. Stinis
Tony Chiang
313
6
0
28 Oct 2023
How many Neurons do we need? A refined Analysis for Shallow Networks trained with Gradient Descent
Journal of Statistical Planning and Inference (JSPI), 2023
Mike Nguyen
Nicole Mücke
MLT
326
8
0
14 Sep 2023
On the Equivalence between Implicit and Explicit Neural Networks: A High-dimensional Viewpoint
Zenan Ling
Zhenyu Liao
Robert C. Qiu
330
0
0
31 Aug 2023
Six Lectures on Linearized Neural Networks
Journal of Statistical Mechanics: Theory and Experiment (J. Stat. Mech.), 2023
Theodor Misiakiewicz
Andrea Montanari
398
18
0
25 Aug 2023
Fundamental limits of overparametrized shallow neural networks for supervised learning
Francesco Camilli
D. Tieplova
Jean Barbier
269
11
0
11 Jul 2023
Deterministic equivalent of the Conjugate Kernel matrix associated to Artificial Neural Networks
Clément Chouard
280
3
0
09 Jun 2023
How Spurious Features Are Memorized: Precise Analysis for Random and NTK Features
International Conference on Machine Learning (ICML), 2023
Simone Bombari
Marco Mondelli
AAML
594
9
0
20 May 2023
Better NTK Conditioning: A Free Lunch from (ReLU) Nonlinear Activation in Wide Neural Networks
Chaoyue Liu
Han Bi
Like Hui
Xiao Liu
MLT
357
9
0
15 May 2023
On the Eigenvalue Decay Rates of a Class of Neural-Network Related Kernel Functions Defined on General Domains
Journal of machine learning research (JMLR), 2023
Yicheng Li
Zixiong Yu
Y. Cotronis
Qian Lin
501
27
0
04 May 2023
Precise Asymptotic Analysis of Deep Random Feature Models
Annual Conference Computational Learning Theory (COLT), 2023
David Bosch
Ashkan Panahi
B. Hassibi
404
21
0
13 Feb 2023
Beyond the Universal Law of Robustness: Sharper Laws for Random Features and Neural Tangent Kernels
International Conference on Machine Learning (ICML), 2023
Simone Bombari
Shayan Kiyani
Marco Mondelli
AAML
524
13
0
03 Feb 2023
Deterministic equivalent and error universality of deep random features learning
International Conference on Machine Learning (ICML), 2023
Dominik Schröder
Hugo Cui
Daniil Dmitriev
Bruno Loureiro
MLT
356
36
0
01 Feb 2023
Bayes-optimal Learning of Deep Random Networks of Extensive-width
International Conference on Machine Learning (ICML), 2023
Hugo Cui
Florent Krzakala
Lenka Zdeborová
BDL
505
49
0
01 Feb 2023
Characterizing the Spectrum of the NTK via a Power Series Expansion
International Conference on Learning Representations (ICLR), 2022
Michael Murray
Hui Jin
Benjamin Bowman
Guido Montúfar
496
20
0
15 Nov 2022
Spectral Evolution and Invariance in Linear-width Neural Networks
Neural Information Processing Systems (NeurIPS), 2022
Zhichao Wang
A. Engel
Anand D. Sarwate
Ioana Dumitriu
Tony Chiang
317
29
0
11 Nov 2022
Overparameterized random feature regression with nearly orthogonal data
International Conference on Artificial Intelligence and Statistics (AISTATS), 2022
Zhichao Wang
Yizhe Zhu
446
9
0
11 Nov 2022
Monotonicity and Double Descent in Uncertainty Estimation with Gaussian Processes
International Conference on Machine Learning (ICML), 2022
Liam Hodgkinson
Christopher van der Heide
Fred Roosta
Michael W. Mahoney
UQCV
301
8
0
14 Oct 2022
On skip connections and normalisation layers in deep optimisation
Neural Information Processing Systems (NeurIPS), 2022
L. MacDonald
Jack Valmadre
Hemanth Saratchandran
Simon Lucey
ODL
531
7
0
10 Oct 2022
Behind the Scenes of Gradient Descent: A Trajectory Analysis via Basis Function Decomposition
International Conference on Learning Representations (ICLR), 2022
Jianhao Ma
Li-Zhen Guo
Salar Fattahi
448
4
0
01 Oct 2022
Spectral Bias Outside the Training Set for Deep Networks in the Kernel Regime
Neural Information Processing Systems (NeurIPS), 2022
Benjamin Bowman
Guido Montúfar
308
17
0
06 Jun 2022
TorchNTK: A Library for Calculation of Neural Tangent Kernels of PyTorch Models
A. Engel
Zhichao Wang
Anand D. Sarwate
Sutanay Choudhury
Tony Chiang
267
3
0
24 May 2022
Memorization and Optimization in Deep Neural Networks with Minimum Over-parameterization
Neural Information Processing Systems (NeurIPS), 2022
Simone Bombari
Mohammad Hossein Amani
Marco Mondelli
466
38
0
20 May 2022
High-dimensional Asymptotics of Feature Learning: How One Gradient Step Improves the Representation
Neural Information Processing Systems (NeurIPS), 2022
Jimmy Ba
Murat A. Erdogdu
Taiji Suzuki
Zhichao Wang
Denny Wu
Greg Yang
MLT
312
143
0
03 May 2022
Meta-free few-shot learning via representation learning with weight averaging
IEEE International Joint Conference on Neural Network (IJCNN), 2022
Kuilin Chen
Chi-Guhn Lee
276
6
0
26 Apr 2022
Concentration of Random Feature Matrices in High-Dimensions
Mathematical and Scientific Machine Learning (MSML), 2022
Zhijun Chen
Hayden Schaeffer
Rachel A. Ward
461
8
0
14 Apr 2022
Explicitising The Implicit Intrepretability of Deep Neural Networks Via Duality
Chandrashekar Lakshminarayanan
Ashutosh Kumar Singh
A. Rajkumar
AI4CE
245
1
0
01 Mar 2022
Largest Eigenvalues of the Conjugate Kernel of Single-Layered Neural Networks
L. Benigni
Sandrine Péché
322
11
0
13 Jan 2022
Random matrices in service of ML footprint: ternary random features with no performance loss
Hafiz Tiomoko Ali
Zhenyu Liao
Romain Couillet
331
7
0
05 Oct 2021
Deformed semicircle law and concentration of nonlinear random matrices for ultra-wide neural networks
Zhichao Wang
Yizhe Zhu
369
27
0
20 Sep 2021
Node Feature Kernels Increase Graph Convolutional Network Robustness
Abdalgader Abubaker
Changmin Wu
J. Lutzeyer
Michalis Vazirgiannis
AAML
405
9
0
04 Sep 2021
1
2
Next
Page 1 of 2
