Bayesian Deep Convolutional Networks with Many Channels are Gaussian Processes

11 October 2018

Jascha Narain Sohl-Dickstein

UQCV

BDL

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Papers citing "Bayesian Deep Convolutional Networks with Many Channels are Gaussian Processes"

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Title
Channel Estimation by Infinite Width Convolutional Networks Mohammed Mallik Guillaume Villemaud 19 0 0 11 Apr 2025
Conditional Temporal Neural Processes with Covariance Loss Boseon Yoo Jiwoo Lee Janghoon Ju Seijun Chung Soyeon Kim Jaesik Choi 70 15 0 01 Apr 2025
A Gap Between the Gaussian RKHS and Neural Networks: An Infinite-Center Asymptotic Analysis Akash Kumar Rahul Parhi Mikhail Belkin 43 0 0 22 Feb 2025
Student-t processes as infinite-width limits of posterior Bayesian neural networks Francesco Caporali Stefano Favaro Dario Trevisan BDL 179 0 0 06 Feb 2025
Proportional infinite-width infinite-depth limit for deep linear neural networks Federico Bassetti Lucia Ladelli P. Rotondo 75 1 0 22 Nov 2024
Stochastic Kernel Regularisation Improves Generalisation in Deep Kernel Machines Edward Milsom Ben Anson Laurence Aitchison 28 0 0 08 Oct 2024
Function-Space MCMC for Bayesian Wide Neural Networks Lucia Pezzetti Stefano Favaro Stefano Peluchetti BDL 130 0 0 26 Aug 2024
DKL-KAN: Scalable Deep Kernel Learning using Kolmogorov-Arnold Networks Shrenik Zinage Sudeepta Mondal S. Sarkar 43 6 0 30 Jul 2024
Finite Neural Networks as Mixtures of Gaussian Processes: From Provable Error Bounds to Prior Selection Steven Adams A. Patané Morteza Lahijanian Luca Laurenti BDL 36 2 0 26 Jul 2024
ForecastGrapher: Redefining Multivariate Time Series Forecasting with Graph Neural Networks Wanlin Cai Kun Wang Hao Wu Xiaoxu Chen Yuankai Wu AI4TS 24 0 0 28 May 2024
Bayesian RG Flow in Neural Network Field Theories Jessica N. Howard Marc S. Klinger Anindita Maiti A. G. Stapleton 68 1 0 27 May 2024
Novel Kernel Models and Exact Representor Theory for Neural Networks Beyond the Over-Parameterized Regime A. Shilton Sunil R. Gupta Santu Rana Svetha Venkatesh 34 0 0 24 May 2024
Random ReLU Neural Networks as Non-Gaussian Processes Rahul Parhi Pakshal Bohra Ayoub El Biari Mehrsa Pourya Michael Unser 63 1 0 16 May 2024
Wilsonian Renormalization of Neural Network Gaussian Processes Jessica N. Howard Ro Jefferson Anindita Maiti Z. Ringel BDL 72 3 0 09 May 2024
Tensor Network-Constrained Kernel Machines as Gaussian Processes Frederiek Wesel Kim Batselier 22 0 0 28 Mar 2024
A Unified Kernel for Neural Network Learning Shao-Qun Zhang Zong-Yi Chen Yong-Ming Tian Xun Lu 29 1 0 26 Mar 2024
NTK-Guided Few-Shot Class Incremental Learning Jingren Liu Zhong Ji Yanwei Pang Yunlong Yu CLL 34 3 0 19 Mar 2024
Neural Networks Asymptotic Behaviours for the Resolution of Inverse Problems L. Debbio Manuel Naviglio Francesco Tarantelli 17 0 0 14 Feb 2024
Flexible infinite-width graph convolutional networks and the importance of representation learning Ben Anson Edward Milsom Laurence Aitchison SSL GNN 24 1 0 09 Feb 2024
Towards Understanding Inductive Bias in Transformers: A View From Infinity Itay Lavie Guy Gur-Ari Z. Ringel 32 1 0 07 Feb 2024
A Survey on Statistical Theory of Deep Learning: Approximation, Training Dynamics, and Generative Models Namjoon Suh Guang Cheng MedIm 27 12 0 14 Jan 2024
A note on regularised NTK dynamics with an application to PAC-Bayesian training Eugenio Clerico Benjamin Guedj 33 0 0 20 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 13 5 0 28 Oct 2023
On the Neural Tangent Kernel of Equilibrium Models Zhili Feng J. Zico Kolter 18 6 0 21 Oct 2023
Wide Neural Networks as Gaussian Processes: Lessons from Deep Equilibrium Models Tianxiang Gao Xiaokai Huo Hailiang Liu Hongyang Gao BDL 17 8 0 16 Oct 2023
Theoretical Analysis of Robust Overfitting for Wide DNNs: An NTK Approach Shaopeng Fu Di Wang AAML 30 1 0 09 Oct 2023
Grokking as a First Order Phase Transition in Two Layer Networks Noa Rubin Inbar Seroussi Z. Ringel 37 15 0 05 Oct 2023
Leave-one-out Distinguishability in Machine Learning Jiayuan Ye Anastasia Borovykh Soufiane Hayou Reza Shokri 33 9 0 29 Sep 2023
A Primer on Bayesian Neural Networks: Review and Debates Federico Danieli Konstantinos Pitas M. Vladimirova Vincent Fortuin BDL AAML 56 18 0 28 Sep 2023
Convolutional Deep Kernel Machines Edward Milsom Ben Anson Laurence Aitchison BDL 23 5 0 18 Sep 2023
Connecting NTK and NNGP: A Unified Theoretical Framework for Wide Neural Network Learning Dynamics Yehonatan Avidan Qianyi Li H. Sompolinsky 60 8 0 08 Sep 2023
Les Houches Lectures on Deep Learning at Large & Infinite Width Yasaman Bahri Boris Hanin Antonin Brossollet Vittorio Erba Christian Keup Rosalba Pacelli James B. Simon AI4CE 12 2 0 04 Sep 2023
Six Lectures on Linearized Neural Networks Theodor Misiakiewicz Andrea Montanari 34 12 0 25 Aug 2023
Local Kernel Renormalization as a mechanism for feature learning in overparametrized Convolutional Neural Networks R. Aiudi R. Pacelli A. Vezzani R. Burioni P. Rotondo MLT 21 15 0 21 Jul 2023
Spectral-Bias and Kernel-Task Alignment in Physically Informed Neural Networks Inbar Seroussi Asaf Miron Z. Ringel PINN 37 0 0 12 Jul 2023
Fundamental limits of overparametrized shallow neural networks for supervised learning Francesco Camilli D. Tieplova Jean Barbier 30 9 0 11 Jul 2023
Neural Hilbert Ladders: Multi-Layer Neural Networks in Function Space Zhengdao Chen 35 1 0 03 Jul 2023
Initial Guessing Bias: How Untrained Networks Favor Some Classes Emanuele Francazi Aurélien Lucchi M. Baity-Jesi AI4CE 20 3 0 01 Jun 2023
An Improved Variational Approximate Posterior for the Deep Wishart Process Sebastian W. Ober Ben Anson Edward Milsom Laurence Aitchison BDL 29 5 0 23 May 2023
Squared Neural Families: A New Class of Tractable Density Models Russell Tsuchida Cheng Soon Ong Dino Sejdinovic TPM 26 11 0 22 May 2023
Posterior Inference on Shallow Infinitely Wide Bayesian Neural Networks under Weights with Unbounded Variance Jorge Loría A. Bhadra UQCV BDL 26 1 0 18 May 2023
Non-asymptotic approximations of Gaussian neural networks via second-order Poincaré inequalities Alberto Bordino Stefano Favaro S. Fortini 18 7 0 08 Apr 2023
Neural signature kernels as infinite-width-depth-limits of controlled ResNets Nicola Muca Cirone M. Lemercier C. Salvi 16 23 0 30 Mar 2023
Inferring networks from time series: a neural approach Thomas Gaskin G. Pavliotis Mark Girolami AI4TS 29 7 0 30 Mar 2023
Online Learning for the Random Feature Model in the Student-Teacher Framework Roman Worschech B. Rosenow 38 0 0 24 Mar 2023
Kernel Regression with Infinite-Width Neural Networks on Millions of Examples Ben Adlam Jaehoon Lee Shreyas Padhy Zachary Nado Jasper Snoek 15 11 0 09 Mar 2023
Guided Deep Kernel Learning Idan Achituve Gal Chechik Ethan Fetaya BDL 31 5 0 19 Feb 2023
Graph Neural Network-Inspired Kernels for Gaussian Processes in Semi-Supervised Learning Zehao Niu M. Anitescu Jing Chen BDL 19 4 0 12 Feb 2023
A Simple Algorithm For Scaling Up Kernel Methods Tengyu Xu Bryan T. Kelly Semyon Malamud 11 0 0 26 Jan 2023
Statistical Physics of Deep Neural Networks: Initialization toward Optimal Channels Kangyu Weng Aohua Cheng Ziyang Zhang Pei Sun Yang Tian 48 2 0 04 Dec 2022