ResearchTrend.AI
Out-of-Distribution Generalization in Kernel Regression
v1v2v3 (latest)

Out-of-Distribution Generalization in Kernel Regression

Abdulkadir Canatar
Blake Bordelon
Cengiz Pehlevan
ArXiv (abs)PDFHTML

Papers citing "Out-of-Distribution Generalization in Kernel Regression"

10 / 10 papers shown
Title
Risk and cross validation in ridge regression with correlated samples
Risk and cross validation in ridge regression with correlated samples
Alexander B. Atanasov
Jacob A. Zavatone-Veth
Cengiz Pehlevan
103
5
0
08 Aug 2024
Benchmarking Out-of-Distribution Generalization Capabilities of DNN-based Encoding Models for the Ventral Visual Cortex
Benchmarking Out-of-Distribution Generalization Capabilities of DNN-based Encoding Models for the Ventral Visual Cortex
Spandan Madan
Will Xiao
Mingran Cao
Hanspeter Pfister
Margaret Livingstone
Gabriel Kreiman
OOD
107
4
0
16 Jun 2024
When does compositional structure yield compositional generalization? A kernel theory
When does compositional structure yield compositional generalization? A kernel theory
Samuel Lippl
Kim Stachenfeld
NAICoGe
255
10
0
26 May 2024
Towards Understanding Inductive Bias in Transformers: A View From Infinity
Towards Understanding Inductive Bias in Transformers: A View From Infinity
Itay Lavie
Guy Gur-Ari
Zohar Ringel
70
1
0
07 Feb 2024
A Spectral Theory of Neural Prediction and Alignment
A Spectral Theory of Neural Prediction and Alignment
Abdulkadir Canatar
J. Feather
Albert J. Wakhloo
SueYeon Chung
OOD
79
15
0
22 Sep 2023
Eight challenges in developing theory of intelligence
Eight challenges in developing theory of intelligence
Haiping Huang
98
7
0
20 Jun 2023
Sparsity-depth Tradeoff in Infinitely Wide Deep Neural Networks
Sparsity-depth Tradeoff in Infinitely Wide Deep Neural Networks
Chanwoo Chun
Daniel D. Lee
BDL
72
2
0
17 May 2023
Learning curves for deep structured Gaussian feature models
Learning curves for deep structured Gaussian feature models
Jacob A. Zavatone-Veth
Cengiz Pehlevan
MLT
92
11
0
01 Mar 2023
Bounding generalization error with input compression: An empirical study with infinite-width networks
Bounding generalization error with input compression: An empirical study with infinite-width networks
A. Galloway
A. Golubeva
Mahmoud Salem
Mihai Nica
Yani Andrew Ioannou
Graham W. Taylor
MLTAI4CE
76
4
0
19 Jul 2022
Dimensionality Reduction and Wasserstein Stability for Kernel Regression
Dimensionality Reduction and Wasserstein Stability for Kernel Regression
Stephan Eckstein
Armin Iske
Mathias Trabs
44
4
0
17 Mar 2022