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1711.00165
Cited By
Deep Neural Networks as Gaussian Processes
1 November 2017
Jaehoon Lee
Yasaman Bahri
Roman Novak
S. Schoenholz
Jeffrey Pennington
Jascha Narain Sohl-Dickstein
UQCV
BDL
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Papers citing
"Deep Neural Networks as Gaussian Processes"
50 / 692 papers shown
Title
Towards a Unified Framework for Uncertainty-aware Nonlinear Variable Selection with Theoretical Guarantees
Wenying Deng
Beau Coker
Rajarshi Mukherjee
J. Liu
B. Coull
21
2
0
15 Apr 2022
Single-level Adversarial Data Synthesis based on Neural Tangent Kernels
Yu-Rong Zhang
Ruei-Yang Su
Sheng-Yen Chou
Shan Wu
GAN
18
2
0
08 Apr 2022
Analytic theory for the dynamics of wide quantum neural networks
Junyu Liu
K. Najafi
Kunal Sharma
F. Tacchino
Liang Jiang
Antonio Mezzacapo
36
52
0
30 Mar 2022
Bayesian Deep Learning with Multilevel Trace-class Neural Networks
Neil K. Chada
Ajay Jasra
K. Law
Sumeetpal S. Singh
BDL
UQCV
83
3
0
24 Mar 2022
On the (Non-)Robustness of Two-Layer Neural Networks in Different Learning Regimes
Elvis Dohmatob
A. Bietti
AAML
39
13
0
22 Mar 2022
Origami in N dimensions: How feed-forward networks manufacture linear separability
Christian Keup
M. Helias
13
8
0
21 Mar 2022
A Framework and Benchmark for Deep Batch Active Learning for Regression
David Holzmüller
Viktor Zaverkin
Johannes Kastner
Ingo Steinwart
UQCV
BDL
GP
31
34
0
17 Mar 2022
Scalable marginalization of correlated latent variables with applications to learning particle interaction kernels
Mengyang Gu
Xubo Liu
X. Fang
Sui Tang
21
8
0
16 Mar 2022
On Connecting Deep Trigonometric Networks with Deep Gaussian Processes: Covariance, Expressivity, and Neural Tangent Kernel
Chi-Ken Lu
Patrick Shafto
BDL
34
0
0
14 Mar 2022
Quantitative Gaussian Approximation of Randomly Initialized Deep Neural Networks
Andrea Basteri
Dario Trevisan
BDL
34
20
0
14 Mar 2022
Deep Regression Ensembles
Antoine Didisheim
Bryan Kelly
Semyon Malamud
UQCV
25
4
0
10 Mar 2022
Revealing the Excitation Causality between Climate and Political Violence via a Neural Forward-Intensity Poisson Process
S. Sun
Bailu Jin
Zhuangkun Wei
Weisi Guo
32
3
0
09 Mar 2022
Tensor Programs V: Tuning Large Neural Networks via Zero-Shot Hyperparameter Transfer
Greg Yang
J. E. Hu
Igor Babuschkin
Szymon Sidor
Xiaodong Liu
David Farhi
Nick Ryder
J. Pachocki
Weizhu Chen
Jianfeng Gao
33
149
0
07 Mar 2022
Generalization Through The Lens Of Leave-One-Out Error
Gregor Bachmann
Thomas Hofmann
Aurelien Lucchi
72
7
0
07 Mar 2022
An Analysis of Ensemble Sampling
Chao Qin
Zheng Wen
Xiuyuan Lu
Benjamin Van Roy
34
21
0
02 Mar 2022
Contrasting random and learned features in deep Bayesian linear regression
Jacob A. Zavatone-Veth
William L. Tong
Cengiz Pehlevan
BDL
MLT
38
27
0
01 Mar 2022
Explicitising The Implicit Intrepretability of Deep Neural Networks Via Duality
Chandrashekar Lakshminarayanan
Ashutosh Kumar Singh
A. Rajkumar
AI4CE
31
1
0
01 Mar 2022
Embedded Ensembles: Infinite Width Limit and Operating Regimes
Maksim Velikanov
Roma Kail
Ivan Anokhin
Roman Vashurin
Maxim Panov
Alexey Zaytsev
Dmitry Yarotsky
25
1
0
24 Feb 2022
A duality connecting neural network and cosmological dynamics
Sven Krippendorf
M. Spannowsky
AI4CE
42
8
0
22 Feb 2022
UncertaINR: Uncertainty Quantification of End-to-End Implicit Neural Representations for Computed Tomography
Francisca Vasconcelos
Bobby He
Nalini Singh
Yee Whye Teh
BDL
OOD
UQCV
37
12
0
22 Feb 2022
Learning from Randomly Initialized Neural Network Features
Ehsan Amid
Rohan Anil
W. Kotłowski
Manfred K. Warmuth
MLT
35
14
0
13 Feb 2022
Decomposing neural networks as mappings of correlation functions
Kirsten Fischer
Alexandre René
Christian Keup
Moritz Layer
David Dahmen
M. Helias
FAtt
22
14
0
10 Feb 2022
Multi-model Ensemble Analysis with Neural Network Gaussian Processes
Trevor Harris
Yangqiu Song
Ryan Sriver
27
5
0
08 Feb 2022
Lossy Gradient Compression: How Much Accuracy Can One Bit Buy?
Sadaf Salehkalaibar
Stefano Rini
FedML
35
4
0
06 Feb 2022
Learning Representation from Neural Fisher Kernel with Low-rank Approximation
Ruixiang Zhang
Shuangfei Zhai
Etai Littwin
J. Susskind
SSL
36
3
0
04 Feb 2022
Deep Layer-wise Networks Have Closed-Form Weights
Chieh-Tsai Wu
A. Masoomi
Arthur Gretton
Jennifer Dy
34
3
0
01 Feb 2022
Stochastic Neural Networks with Infinite Width are Deterministic
Liu Ziyin
Hanlin Zhang
Xiangming Meng
Yuting Lu
Eric P. Xing
Masakuni Ueda
41
3
0
30 Jan 2022
How does unlabeled data improve generalization in self-training? A one-hidden-layer theoretical analysis
Shuai Zhang
Ming Wang
Sijia Liu
Pin-Yu Chen
Jinjun Xiong
SSL
MLT
41
23
0
21 Jan 2022
Kernel Methods and Multi-layer Perceptrons Learn Linear Models in High Dimensions
Mojtaba Sahraee-Ardakan
M. Emami
Parthe Pandit
S. Rangan
A. Fletcher
41
9
0
20 Jan 2022
Adaptive Transfer Learning for Plant Phenotyping
Jun Wu
Elizabeth Ainsworth
Sheng Wang
K. Guan
Jingrui He
6
2
0
14 Jan 2022
On neural network kernels and the storage capacity problem
Jacob A. Zavatone-Veth
Cengiz Pehlevan
19
6
0
12 Jan 2022
Complexity from Adaptive-Symmetries Breaking: Global Minima in the Statistical Mechanics of Deep Neural Networks
Shaun Li
AI4CE
51
0
0
03 Jan 2022
Separation of Scales and a Thermodynamic Description of Feature Learning in Some CNNs
Inbar Seroussi
Gadi Naveh
Zohar Ringel
43
51
0
31 Dec 2021
NN2Poly: A polynomial representation for deep feed-forward artificial neural networks
Pablo Morala
Jenny Alexandra Cifuentes
R. Lillo
Iñaki Ucar
32
6
0
21 Dec 2021
Revisiting Memory Efficient Kernel Approximation: An Indefinite Learning Perspective
Simon Heilig
Maximilian Münch
Frank-Michael Schleif
33
1
0
18 Dec 2021
Posterior contraction rates for constrained deep Gaussian processes in density estimation and classication
François Bachoc
A. Lagnoux
34
4
0
14 Dec 2021
Eigenspace Restructuring: a Principle of Space and Frequency in Neural Networks
Lechao Xiao
39
22
0
10 Dec 2021
Faster Single-loop Algorithms for Minimax Optimization without Strong Concavity
Junchi Yang
Antonio Orvieto
Aurelien Lucchi
Niao He
27
62
0
10 Dec 2021
Provable Continual Learning via Sketched Jacobian Approximations
Reinhard Heckel
CLL
20
9
0
09 Dec 2021
Infinite Neural Network Quantum States: Entanglement and Training Dynamics
Di Luo
James Halverson
32
6
0
01 Dec 2021
Dependence between Bayesian neural network units
M. Vladimirova
Julyan Arbel
Stéphane Girard
BDL
28
3
0
29 Nov 2021
Impact of classification difficulty on the weight matrices spectra in Deep Learning and application to early-stopping
Xuran Meng
Jianfeng Yao
34
7
0
26 Nov 2021
Critical Initialization of Wide and Deep Neural Networks through Partial Jacobians: General Theory and Applications
Darshil Doshi
Tianyu He
Andrey Gromov
32
8
0
23 Nov 2021
Depth induces scale-averaging in overparameterized linear Bayesian neural networks
Jacob A. Zavatone-Veth
Cengiz Pehlevan
BDL
UQCV
MDE
46
9
0
23 Nov 2021
On the Equivalence between Neural Network and Support Vector Machine
Yilan Chen
Wei Huang
Lam M. Nguyen
Tsui-Wei Weng
AAML
25
18
0
11 Nov 2021
Empirical analysis of representation learning and exploration in neural kernel bandits
Michal Lisicki
Arash Afkanpour
Graham W. Taylor
26
0
0
05 Nov 2021
Dynamics of Local Elasticity During Training of Neural Nets
Soham Dan
Anirbit Mukherjee
Avirup Das
Phanideep Gampa
25
0
0
01 Nov 2021
Geometry-Aware Hierarchical Bayesian Learning on Manifolds
Yonghui Fan
Yalin Wang
18
2
0
30 Oct 2021
PAC-Bayesian Learning of Aggregated Binary Activated Neural Networks with Probabilities over Representations
Louis Fortier-Dubois
Gaël Letarte
Benjamin Leblanc
Franccois Laviolette
Pascal Germain
UQCV
19
0
0
28 Oct 2021
Periodic Activation Functions Induce Stationarity
Lassi Meronen
Martin Trapp
Arno Solin
BDL
25
20
0
26 Oct 2021
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