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Deep Neural Networks as Gaussian Processes

1 November 2017

Jascha Narain Sohl-Dickstein

UQCV

BDL

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Papers citing "Deep Neural Networks as Gaussian Processes"

50 / 696 papers shown

Title
Efficient Uncertainty Estimation with Gaussian Process for Reliable Dialog Response Retrieval Tong Ye Zhitao Li Jianzong Wang Ning Cheng Jing Xiao BDL 54 1 0 15 Mar 2023
Kernel Regression with Infinite-Width Neural Networks on Millions of Examples Ben Adlam Jaehoon Lee Shreyas Padhy Zachary Nado Jasper Snoek 84 12 0 09 Mar 2023
Bayesian inference with finitely wide neural networks Chi-Ken Lu BDL 89 0 0 06 Mar 2023
Phase diagram of early training dynamics in deep neural networks: effect of the learning rate, depth, and width Dayal Singh Kalra M. Barkeshli 137 9 0 23 Feb 2023
Heterogeneous Neuronal and Synaptic Dynamics for Spike-Efficient Unsupervised Learning: Theory and Design Principles Biswadeep Chakraborty Saibal Mukhopadhyay 96 10 0 22 Feb 2023
Deep Transformers without Shortcuts: Modifying Self-attention for Faithful Signal Propagation Bobby He James Martens Guodong Zhang Aleksandar Botev Andy Brock Samuel L. Smith Yee Whye Teh 92 30 0 20 Feb 2023
Guided Deep Kernel Learning Idan Achituve Gal Chechik Ethan Fetaya BDL 66 7 0 19 Feb 2023
The Geometry of Neural Nets' Parameter Spaces Under Reparametrization Agustinus Kristiadi Felix Dangel Philipp Hennig 73 14 0 14 Feb 2023
Density-Softmax: Efficient Test-time Model for Uncertainty Estimation and Robustness under Distribution Shifts H. Bui Anqi Liu OOD UQCV 199 6 0 13 Feb 2023
Precise Asymptotic Analysis of Deep Random Feature Models David Bosch Ashkan Panahi B. Hassibi 110 19 0 13 Feb 2023
Graph Neural Network-Inspired Kernels for Gaussian Processes in Semi-Supervised Learning Zehao Niu M. Anitescu Jing Chen BDL 50 5 0 12 Feb 2023
Gaussian Process-Gated Hierarchical Mixtures of Experts Yuhao Liu Marzieh Ajirak Petar M. Djurić MoE 80 1 0 09 Feb 2023
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 132 17 0 06 Feb 2023
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 147 2 0 02 Feb 2023
Width and Depth Limits Commute in Residual Networks Soufiane Hayou Greg Yang 90 14 0 01 Feb 2023
Deterministic equivalent and error universality of deep random features learning Dominik Schröder Hugo Cui Daniil Dmitriev Bruno Loureiro MLT 114 29 0 01 Feb 2023
Bayes-optimal Learning of Deep Random Networks of Extensive-width Hugo Cui Florent Krzakala Lenka Zdeborová BDL 124 39 0 01 Feb 2023
Gradient Descent in Neural Networks as Sequential Learning in RKBS A. Shilton Sunil R. Gupta Santu Rana Svetha Venkatesh MLT 148 1 0 01 Feb 2023
Deep networks for system identification: a Survey G. Pillonetto Aleksandr Aravkin Daniel Gedon L. Ljung Antônio H. Ribeiro Thomas B. Schon OOD 113 45 0 30 Jan 2023
A Simple Algorithm For Scaling Up Kernel Methods Tengyu Xu Bryan Kelly Semyon Malamud 77 0 0 26 Jan 2023
Neural networks learn to magnify areas near decision boundaries Jacob A. Zavatone-Veth Sheng Yang Julian Rubinfien Cengiz Pehlevan MLT AI4CE 91 6 0 26 Jan 2023
Estimating Causal Effects using a Multi-task Deep Ensemble Ziyang Jiang Zhuoran Hou Yi-Ling Liu Yiman Ren Keyu Li David Carlson CML 93 6 0 26 Jan 2023
M22: A Communication-Efficient Algorithm for Federated Learning Inspired by Rate-Distortion Yangyi Liu Stefano Rini Sadaf Salehkalaibar Jun Chen FedML 61 4 0 23 Jan 2023
Towards Quantification of Assurance for Learning-enabled Components Erfan Asaadi E. Denney Ganesh J. Pai 47 11 0 21 Jan 2023
Catapult Dynamics and Phase Transitions in Quadratic Nets David Meltzer Junyu Liu 79 9 0 18 Jan 2023
Dataset Distillation: A Comprehensive Review Ruonan Yu Songhua Liu Xinchao Wang DD 176 132 0 17 Jan 2023
Smooth Mathematical Function from Compact Neural Networks I. K. Hong 63 0 0 31 Dec 2022
Bayesian Interpolation with Deep Linear Networks Boris Hanin Alexander Zlokapa 153 26 0 29 Dec 2022
Statistical Physics of Deep Neural Networks: Initialization toward Optimal Channels Kangyu Weng Aohua Cheng Ziyang Zhang Pei Sun Yang Tian 115 2 0 04 Dec 2022
Applications of AI in Astronomy S. Djorgovski Ashish Mahabal Matthew Graham K. Polsterer A. Krone-Martins 71 2 0 03 Dec 2022
Diffusion Probabilistic Model Made Slim Xingyi Yang Daquan Zhou Jiashi Feng Xinchao Wang DiffM 115 111 0 27 Nov 2022
A Kernel Perspective of Skip Connections in Convolutional Networks Daniel Barzilai Amnon Geifman Meirav Galun Ronen Basri 73 13 0 27 Nov 2022
Simple initialization and parametrization of sinusoidal networks via their kernel bandwidth Filipe de Avila Belbute-Peres J. Zico Kolter 67 2 0 26 Nov 2022
Multiple Imputation with Neural Network Gaussian Process for High-dimensional Incomplete Data Zongyu Dai Zhiqi Bu Q. Long 78 4 0 23 Nov 2022
Simplicity Bias in Transformers and their Ability to Learn Sparse Boolean Functions S. Bhattamishra Arkil Patel Varun Kanade Phil Blunsom 136 49 0 22 Nov 2022
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 76 2 0 16 Nov 2022
Characterizing the Spectrum of the NTK via a Power Series Expansion Michael Murray Hui Jin Benjamin Bowman Guido Montúfar 107 11 0 15 Nov 2022
Spectral Evolution and Invariance in Linear-width Neural Networks Zhichao Wang A. Engel Anand D. Sarwate Ioana Dumitriu Tony Chiang 118 18 0 11 Nov 2022
Overparameterized random feature regression with nearly orthogonal data Zhichao Wang Yizhe Zhu 88 4 0 11 Nov 2022
UATTA-ENS: Uncertainty Aware Test Time Augmented Ensemble for PIRC Diabetic Retinopathy Detection Pratinav Seth Adil Mehmood Khan Ananya Gupta Saurabh Mishra Akshat Bhandhari 79 0 0 06 Nov 2022
Globally Gated Deep Linear Networks Qianyi Li H. Sompolinsky AI4CE 81 11 0 31 Oct 2022
A Solvable Model of Neural Scaling Laws A. Maloney Daniel A. Roberts J. Sully 126 57 0 30 Oct 2022
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 55 6 0 23 Oct 2022
Efficient Dataset Distillation Using Random Feature Approximation Noel Loo Ramin Hasani Alexander Amini Daniela Rus DD 136 101 0 21 Oct 2022
Evolution of Neural Tangent Kernels under Benign and Adversarial Training Noel Loo Ramin Hasani Alexander Amini Daniela Rus AAML 117 13 0 21 Oct 2022
Global Convergence of SGD On Two Layer Neural Nets Pulkit Gopalani Anirbit Mukherjee 76 6 0 20 Oct 2022
Optimisation & Generalisation in Networks of Neurons Jeremy Bernstein AI4CE 89 2 0 18 Oct 2022
Disentangling the Predictive Variance of Deep Ensembles through the Neural Tangent Kernel Seijin Kobayashi Pau Vilimelis Aceituno J. Oswald UQCV 94 3 0 18 Oct 2022
Analysis of Convolutions, Non-linearity and Depth in Graph Neural Networks using Neural Tangent Kernel Mahalakshmi Sabanayagam Pascal Esser Debarghya Ghoshdastidar 149 2 0 18 Oct 2022
TiDAL: Learning Training Dynamics for Active Learning Seong Min Kye Kwanghee Choi Hyeongmin Byun Buru Chang 96 14 0 13 Oct 2022