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Deep Neural Networks as Gaussian Processes

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
Guided Deep Kernel Learning
Guided Deep Kernel Learning
Idan Achituve
Gal Chechik
Ethan Fetaya
BDL
31
5
0
19 Feb 2023
The Geometry of Neural Nets' Parameter Spaces Under Reparametrization
The Geometry of Neural Nets' Parameter Spaces Under Reparametrization
Agustinus Kristiadi
Felix Dangel
Philipp Hennig
32
11
0
14 Feb 2023
Density-Softmax: Efficient Test-time Model for Uncertainty Estimation
  and Robustness under Distribution Shifts
Density-Softmax: Efficient Test-time Model for Uncertainty Estimation and Robustness under Distribution Shifts
H. Bui
Anqi Liu
OOD
UQCV
23
6
0
13 Feb 2023
Precise Asymptotic Analysis of Deep Random Feature Models
Precise Asymptotic Analysis of Deep Random Feature Models
David Bosch
Ashkan Panahi
B. Hassibi
35
19
0
13 Feb 2023
Graph Neural Network-Inspired Kernels for Gaussian Processes in
  Semi-Supervised Learning
Graph Neural Network-Inspired Kernels for Gaussian Processes in Semi-Supervised Learning
Zehao Niu
M. Anitescu
Jing Chen
BDL
27
4
0
12 Feb 2023
Gaussian Process-Gated Hierarchical Mixtures of Experts
Gaussian Process-Gated Hierarchical Mixtures of Experts
Yuhao Liu
Marzieh Ajirak
Petar M. Djurić
MoE
16
1
0
09 Feb 2023
Joint Edge-Model Sparse Learning is Provably Efficient for Graph Neural
  Networks
Joint Edge-Model Sparse Learning is Provably Efficient for Graph Neural Networks
Shuai Zhang
Ming Wang
Pin-Yu Chen
Sijia Liu
Songtao Lu
Miaoyuan Liu
MLT
29
16
0
06 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
Width and Depth Limits Commute in Residual Networks
Width and Depth Limits Commute in Residual Networks
Soufiane Hayou
Greg Yang
50
14
0
01 Feb 2023
Deterministic equivalent and error universality of deep random features
  learning
Deterministic equivalent and error universality of deep random features learning
Dominik Schröder
Hugo Cui
Daniil Dmitriev
Bruno Loureiro
MLT
39
28
0
01 Feb 2023
Bayes-optimal Learning of Deep Random Networks of Extensive-width
Bayes-optimal Learning of Deep Random Networks of Extensive-width
Hugo Cui
Florent Krzakala
Lenka Zdeborová
BDL
30
35
0
01 Feb 2023
Gradient Descent in Neural Networks as Sequential Learning in RKBS
Gradient Descent in Neural Networks as Sequential Learning in RKBS
A. Shilton
Sunil R. Gupta
Santu Rana
Svetha Venkatesh
MLT
24
1
0
01 Feb 2023
Deep networks for system identification: a Survey
Deep networks for system identification: a Survey
G. Pillonetto
Aleksandr Aravkin
Daniel Gedon
L. Ljung
Antônio H. Ribeiro
Thomas B. Schon
OOD
42
37
0
30 Jan 2023
A Simple Algorithm For Scaling Up Kernel Methods
A Simple Algorithm For Scaling Up Kernel Methods
Tengyu Xu
Bryan Kelly
Semyon Malamud
30
0
0
26 Jan 2023
Neural networks learn to magnify areas near decision boundaries
Neural networks learn to magnify areas near decision boundaries
Jacob A. Zavatone-Veth
Sheng Yang
Julian Rubinfien
Cengiz Pehlevan
MLT
AI4CE
30
6
0
26 Jan 2023
Estimating Causal Effects using a Multi-task Deep Ensemble
Estimating Causal Effects using a Multi-task Deep Ensemble
Ziyang Jiang
Zhuoran Hou
Yi-Ling Liu
Yiman Ren
Keyu Li
David Carlson
CML
26
6
0
26 Jan 2023
M22: A Communication-Efficient Algorithm for Federated Learning Inspired
  by Rate-Distortion
M22: A Communication-Efficient Algorithm for Federated Learning Inspired by Rate-Distortion
Yangyi Liu
Stefano Rini
Sadaf Salehkalaibar
Jun Chen
FedML
21
4
0
23 Jan 2023
Towards Quantification of Assurance for Learning-enabled Components
Towards Quantification of Assurance for Learning-enabled Components
Erfan Asaadi
E. Denney
Ganesh J. Pai
18
11
0
21 Jan 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
Dataset Distillation: A Comprehensive Review
Dataset Distillation: A Comprehensive Review
Ruonan Yu
Songhua Liu
Xinchao Wang
DD
60
121
0
17 Jan 2023
Smooth Mathematical Function from Compact Neural Networks
Smooth Mathematical Function from Compact Neural Networks
I. K. Hong
26
0
0
31 Dec 2022
Bayesian Interpolation with Deep Linear Networks
Bayesian Interpolation with Deep Linear Networks
Boris Hanin
Alexander Zlokapa
49
25
0
29 Dec 2022
Statistical Physics of Deep Neural Networks: Initialization toward
  Optimal Channels
Statistical Physics of Deep Neural Networks: Initialization toward Optimal Channels
Kangyu Weng
Aohua Cheng
Ziyang Zhang
Pei Sun
Yang Tian
58
2
0
04 Dec 2022
Applications of AI in Astronomy
Applications of AI in Astronomy
S. Djorgovski
Ashish Mahabal
Matthew Graham
K. Polsterer
A. Krone-Martins
26
2
0
03 Dec 2022
Diffusion Probabilistic Model Made Slim
Diffusion Probabilistic Model Made Slim
Xingyi Yang
Daquan Zhou
Jiashi Feng
Xinchao Wang
DiffM
29
104
0
27 Nov 2022
A Kernel Perspective of Skip Connections in Convolutional Networks
A Kernel Perspective of Skip Connections in Convolutional Networks
Daniel Barzilai
Amnon Geifman
Meirav Galun
Ronen Basri
23
12
0
27 Nov 2022
Simple initialization and parametrization of sinusoidal networks via
  their kernel bandwidth
Simple initialization and parametrization of sinusoidal networks via their kernel bandwidth
Filipe de Avila Belbute-Peres
J. Zico Kolter
32
2
0
26 Nov 2022
Multiple Imputation with Neural Network Gaussian Process for
  High-dimensional Incomplete Data
Multiple Imputation with Neural Network Gaussian Process for High-dimensional Incomplete Data
Zongyu Dai
Zhiqi Bu
Q. Long
35
4
0
23 Nov 2022
Simplicity Bias in Transformers and their Ability to Learn Sparse
  Boolean Functions
Simplicity Bias in Transformers and their Ability to Learn Sparse Boolean Functions
S. Bhattamishra
Arkil Patel
Varun Kanade
Phil Blunsom
22
46
0
22 Nov 2022
An Empirical Analysis of the Advantages of Finite- v.s. Infinite-Width
  Bayesian Neural Networks
An Empirical Analysis of the Advantages of Finite- v.s. Infinite-Width Bayesian Neural Networks
Jiayu Yao
Yaniv Yacoby
Beau Coker
Weiwei Pan
Finale Doshi-Velez
24
1
0
16 Nov 2022
Characterizing the Spectrum of the NTK via a Power Series Expansion
Characterizing the Spectrum of the NTK via a Power Series Expansion
Michael Murray
Hui Jin
Benjamin Bowman
Guido Montúfar
43
11
0
15 Nov 2022
Spectral Evolution and Invariance in Linear-width Neural Networks
Spectral Evolution and Invariance in Linear-width Neural Networks
Zhichao Wang
A. Engel
Anand D. Sarwate
Ioana Dumitriu
Tony Chiang
45
14
0
11 Nov 2022
Overparameterized random feature regression with nearly orthogonal data
Overparameterized random feature regression with nearly orthogonal data
Zhichao Wang
Yizhe Zhu
31
3
0
11 Nov 2022
UATTA-ENS: Uncertainty Aware Test Time Augmented Ensemble for PIRC
  Diabetic Retinopathy Detection
UATTA-ENS: Uncertainty Aware Test Time Augmented Ensemble for PIRC Diabetic Retinopathy Detection
Pratinav Seth
Adil Mehmood Khan
Ananya Gupta
Saurabh Mishra
Akshat Bhandhari
31
0
0
06 Nov 2022
Globally Gated Deep Linear Networks
Globally Gated Deep Linear Networks
Qianyi Li
H. Sompolinsky
AI4CE
27
10
0
31 Oct 2022
A Solvable Model of Neural Scaling Laws
A Solvable Model of Neural Scaling Laws
A. Maloney
Daniel A. Roberts
J. Sully
52
51
0
30 Oct 2022
Accelerating the training of single-layer binary neural networks using
  the HHL quantum algorithm
Accelerating the training of single-layer binary neural networks using the HHL quantum algorithm
S. L. Alarcón
Cory E. Merkel
Martin Hoffnagle
Sabrina Ly
Alejandro Pozas-Kerstjens
24
5
0
23 Oct 2022
Efficient Dataset Distillation Using Random Feature Approximation
Efficient Dataset Distillation Using Random Feature Approximation
Noel Loo
Ramin Hasani
Alexander Amini
Daniela Rus
DD
81
98
0
21 Oct 2022
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
44
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
31
5
0
20 Oct 2022
Optimisation & Generalisation in Networks of Neurons
Optimisation & Generalisation in Networks of Neurons
Jeremy Bernstein
AI4CE
24
2
0
18 Oct 2022
Disentangling the Predictive Variance of Deep Ensembles through the
  Neural Tangent Kernel
Disentangling the Predictive Variance of Deep Ensembles through the Neural Tangent Kernel
Seijin Kobayashi
Pau Vilimelis Aceituno
J. Oswald
UQCV
31
2
0
18 Oct 2022
Analysis of Convolutions, Non-linearity and Depth in Graph Neural
  Networks using Neural Tangent Kernel
Analysis of Convolutions, Non-linearity and Depth in Graph Neural Networks using Neural Tangent Kernel
Mahalakshmi Sabanayagam
P. Esser
D. Ghoshdastidar
36
2
0
18 Oct 2022
TiDAL: Learning Training Dynamics for Active Learning
TiDAL: Learning Training Dynamics for Active Learning
Seong Min Kye
Kwanghee Choi
Hyeongmin Byun
Buru Chang
34
13
0
13 Oct 2022
Meta-Principled Family of Hyperparameter Scaling Strategies
Meta-Principled Family of Hyperparameter Scaling Strategies
Sho Yaida
58
16
0
10 Oct 2022
Layer Ensembles
Layer Ensembles
Illia Oleksiienko
Alexandros Iosifidis
BDL
UQCV
34
1
0
10 Oct 2022
The Influence of Learning Rule on Representation Dynamics in Wide Neural
  Networks
The Influence of Learning Rule on Representation Dynamics in Wide Neural Networks
Blake Bordelon
Cengiz Pehlevan
41
22
0
05 Oct 2022
Uncertainty-Aware Meta-Learning for Multimodal Task Distributions
Uncertainty-Aware Meta-Learning for Multimodal Task Distributions
Cesar Almecija
Apoorva Sharma
Navid Azizan
OOD
UQCV
26
3
0
04 Oct 2022
On the infinite-depth limit of finite-width neural networks
On the infinite-depth limit of finite-width neural networks
Soufiane Hayou
35
22
0
03 Oct 2022
Joint Embedding Self-Supervised Learning in the Kernel Regime
Joint Embedding Self-Supervised Learning in the Kernel Regime
B. Kiani
Randall Balestriero
Yubei Chen
S. Lloyd
Yann LeCun
SSL
51
13
0
29 Sep 2022
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