Gaussian Process Behaviour in Wide Deep Neural Networks

30 April 2018

Papers citing "Gaussian Process Behaviour in Wide Deep Neural Networks"

50 / 391 papers shown

Title
Information-theoretic reduction of deep neural networks to linear models in the overparametrized proportional regime Francesco Camilli D. Tieplova Eleonora Bergamin Jean Barbier 138 0 0 06 May 2025
Channel Estimation by Infinite Width Convolutional Networks Mohammed Mallik Guillaume Villemaud 24 0 0 11 Apr 2025
Fractal and Regular Geometry of Deep Neural Networks Simmaco Di Lillo Domenico Marinucci Michele Salvi Stefano Vigogna MDE AI4CE 36 0 0 08 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
Deep Neural Nets as Hamiltonians Mike Winer Boris Hanin 160 0 0 31 Mar 2025
The Architecture and Evaluation of Bayesian Neural Networks Alisa Sheinkman Sara Wade UQCV BDL 72 0 0 14 Mar 2025
Uncertainty Quantification From Scaling Laws in Deep Neural Networks Ibrahim Elsharkawy Yonatan Kahn Benjamin Hooberman UQCV 52 0 0 07 Mar 2025
Differential Coding for Training-Free ANN-to-SNN Conversion Zihan Huang Wei Fang Tong Bu Peng Xue Zecheng Hao Xiaohan Yu Yuanhong Tang Zhaofei Yu Tiejun Huang 41 0 0 01 Mar 2025
Feature maps for the Laplacian kernel and its generalizations Sudhendu Ahir Parthe Pandit 65 0 0 24 Feb 2025
Student-t processes as infinite-width limits of posterior Bayesian neural networks Francesco Caporali Stefano Favaro Dario Trevisan BDL 197 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
Variational Bayesian Bow tie Neural Networks with Shrinkage Alisa Sheinkman Sara Wade BDL UQCV 48 0 0 17 Nov 2024
On learning higher-order cumulants in diffusion models Gert Aarts Diaa E. Habibi Lei Wang K. Zhou 26 4 0 28 Oct 2024
A Lipschitz spaces view of infinitely wide shallow neural networks Francesca Bartolucci Marcello Carioni José A. Iglesias Yury Korolev Emanuele Naldi Stefano Vigogna 23 0 0 18 Oct 2024
Correspondence of NNGP Kernel and the Matern Kernel Amanda Muyskens Benjamin W. Priest I. Goumiri M. Schneider BDL 23 1 0 10 Oct 2024
Deep Kernel Posterior Learning under Infinite Variance Prior Weights Jorge Loría A. Bhadra BDL UQCV 66 0 0 02 Oct 2024
Predicting and analyzing memorization within fine-tuned Large Language Models Jérémie Dentan Davide Buscaldi A. Shabou Sonia Vanier 37 0 0 27 Sep 2024
Functional Stochastic Gradient MCMC for Bayesian Neural Networks Mengjing Wu Junyu Xuan Jie Lu BDL 18 0 0 25 Sep 2024
Re-evaluating the Advancements of Heterophilic Graph Learning Sitao Luan Qincheng Lu Chenqing Hua Xinyu Wang Jiaqi Zhu Xiao-Wen Chang 57 2 0 09 Sep 2024
Function-Space MCMC for Bayesian Wide Neural Networks Lucia Pezzetti Stefano Favaro Stefano Peluchetti BDL 162 0 0 26 Aug 2024
Source-Free Domain-Invariant Performance Prediction Ekaterina Khramtsova Mahsa Baktashmotlagh Guido Zuccon Xi Wang Mathieu Salzmann UQCV 48 1 0 05 Aug 2024
DKL-KAN: Scalable Deep Kernel Learning using Kolmogorov-Arnold Networks Shrenik Zinage Sudeepta Mondal S. Sarkar 46 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
A UAV-assisted Wireless Localization Challenge on AERPAW Paul S. Kudyba Jaya Sravani Mandapaka Weijie Wang Logan McCorkendale Zachary McCorkendale ... Eric Adams K. Namuduri Fraida Fund Mihail L. Sichitiu Ozgur Ozdemir 28 2 0 16 Jul 2024
Exploiting the equivalence between quantum neural networks and perceptrons Chris Mingard Jessica Pointing Charles London Yoonsoo Nam Ard A. Louis 40 2 0 05 Jul 2024
Coding schemes in neural networks learning classification tasks Alexander van Meegen H. Sompolinsky 39 6 0 24 Jun 2024
Crafting Heavy-Tails in Weight Matrix Spectrum without Gradient Noise Vignesh Kothapalli Tianyu Pang Shenyang Deng Zongmin Liu Yaoqing Yang 40 3 0 07 Jun 2024
Understanding and Minimising Outlier Features in Neural Network Training Bobby He Lorenzo Noci Daniele Paliotta Imanol Schlag Thomas Hofmann 39 3 0 29 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
Dissecting the Interplay of Attention Paths in a Statistical Mechanics Theory of Transformers Lorenzo Tiberi Francesca Mignacco Kazuki Irie H. Sompolinsky 44 6 0 24 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
Spectral complexity of deep neural networks Simmaco Di Lillo Domenico Marinucci Michele Salvi Stefano Vigogna BDL 82 1 0 15 May 2024
Wilsonian Renormalization of Neural Network Gaussian Processes Jessica N. Howard Ro Jefferson Anindita Maiti Zohar Ringel BDL 80 3 0 09 May 2024
Implicit Neural Representations for Robust Joint Sparse-View CT Reconstruction Jiayang Shi Junyi Zhu D. Pelt K. Batenburg Matthew B. Blaschko 35 3 0 03 May 2024
Tensor Network-Constrained Kernel Machines as Gaussian Processes Frederiek Wesel Kim Batselier 22 0 0 28 Mar 2024
Deep Horseshoe Gaussian Processes Ismael Castillo Thibault Randrianarisoa BDL UQCV 44 5 0 04 Mar 2024
Neural Redshift: Random Networks are not Random Functions Damien Teney A. Nicolicioiu Valentin Hartmann Ehsan Abbasnejad 103 18 0 04 Mar 2024
Asymptotics of Learning with Deep Structured (Random) Features Dominik Schröder Daniil Dmitriev Hugo Cui Bruno Loureiro 56 6 0 21 Feb 2024
Neural Networks Asymptotic Behaviours for the Resolution of Inverse Problems L. Debbio Manuel Naviglio Francesco Tarantelli 17 0 0 14 Feb 2024
Feature Mapping in Physics-Informed Neural Networks (PINNs) Chengxi Zeng T. Burghardt A. Gambaruto 41 1 0 10 Feb 2024
Flexible infinite-width graph convolutional networks and the importance of representation learning Ben Anson Edward Milsom Laurence Aitchison SSL GNN 32 1 0 09 Feb 2024
Position: Bayesian Deep Learning is Needed in the Age of Large-Scale AI Theodore Papamarkou Maria Skoularidou Konstantina Palla Laurence Aitchison Julyan Arbel ... David Rügamer Yee Whye Teh Max Welling Andrew Gordon Wilson Ruqi Zhang UQCV BDL 42 27 0 01 Feb 2024
Improving the Expressive Power of Deep Neural Networks through Integral Activation Transform Zezhong Zhang Feng Bao Guannan Zhang 22 0 0 19 Dec 2023
Wide Deep Neural Networks with Gaussian Weights are Very Close to Gaussian Processes Dario Trevisan UQCV BDL 30 7 0 18 Dec 2023
Duality of Bures and Shape Distances with Implications for Comparing Neural Representations Sarah E. Harvey Brett W. Larsen Alex H. Williams 90 11 0 19 Nov 2023
Simplifying Transformer Blocks Bobby He Thomas Hofmann 27 30 0 03 Nov 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 25 8 0 16 Oct 2023
On permutation symmetries in Bayesian neural network posteriors: a variational perspective Simone Rossi Ankit Singh T. Hannagan 32 2 0 16 Oct 2023