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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"

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Title
The Importance of Being Lazy: Scaling Limits of Continual Learning Jacopo Graldi Alessandro Breccia Giulia Lanzillotta Thomas Hofmann Lorenzo Noci CLL 43 0 0 20 Jun 2025
Flat Channels to Infinity in Neural Loss Landscapes Flavio Martinelli Alexander Van Meegen Berfin Simsek W. Gerstner Johanni Brea 20 0 0 17 Jun 2025
On the Stability of the Jacobian Matrix in Deep Neural Networks Benjamin Dadoun Soufiane Hayou Hanan Salam M. Seddik Pierre Youssef ODL 44 0 0 10 Jun 2025
Attention Retrieves, MLP Memorizes: Disentangling Trainable Components in the Transformer Yihe Dong Lorenzo Noci Mikhail Khodak Mufan Li 74 0 0 01 Jun 2025
Statistical mechanics of extensive-width Bayesian neural networks near interpolation Jean Barbier Francesco Camilli Minh-Toan Nguyen Mauro Pastore Rudy Skerk 49 0 0 30 May 2025
Universal Value-Function Uncertainties Moritz A. Zanger Max Weltevrede Yaniv Oren Pascal R. van der Vaart Caroline Horsch Wendelin Bohmer M. Spaan OffRL 82 0 0 27 May 2025
A ZeNN architecture to avoid the Gaussian trap Luís Carvalho Joao L. Costa José Mourao Gonçalo Oliveira 35 0 0 26 May 2025
Temperature is All You Need for Generalization in Langevin Dynamics and other Markov Processes I. Harel Yonathan Wolanowsky Gal Vardi Nathan Srebro Daniel Soudry AI4CE 105 0 0 25 May 2025
Querying Kernel Methods Suffices for Reconstructing their Training Data Daniel Barzilai Yuval Margalit Eitan Gronich Gilad Yehudai Meirav Galun Ronen Basri 51 0 0 25 May 2025
Critical Points of Random Neural Networks Simmaco Di Lillo 90 0 0 22 May 2025
TULiP: Test-time Uncertainty Estimation via Linearization and Weight Perturbation Yuhui Zhang Dongshen Wu Yuichiro Wada Takafumi Kanamori OODD 249 1 0 22 May 2025
High-Dimensional Analysis of Bootstrap Ensemble Classifiers Hamza Cherkaoui Malik Tiomoko M. Seddik Cosme Louart Ekkehard Schnoor Balázs Kégl 135 0 0 20 May 2025
Just One Layer Norm Guarantees Stable Extrapolation Juliusz Ziomek George Whittle Michael A. Osborne 100 0 0 20 May 2025
Phi: Leveraging Pattern-based Hierarchical Sparsity for High-Efficiency Spiking Neural Networks Chiyue Wei Bowen Duan Cong Guo Jing Zhang Qingyue Song Hai "Helen" Li Yiran Chen 126 0 0 16 May 2025
Slow Transition to Low-Dimensional Chaos in Heavy-Tailed Recurrent Neural Networks Yi Xie Stefan Mihalas Łukasz Kuśmierz 91 0 0 14 May 2025
Information-theoretic reduction of deep neural networks to linear models in the overparametrized proportional regime Francesco Camilli D. Tieplova Eleonora Bergamin Jean Barbier 426 2 0 06 May 2025
On the Importance of Gaussianizing Representations Daniel Eftekhari Vardan Papyan 99 0 0 01 May 2025
Fractal and Regular Geometry of Deep Neural Networks Simmaco Di Lillo Domenico Marinucci Michele Salvi Stefano Vigogna MDE AI4CE 66 1 0 08 Apr 2025
Conditional Temporal Neural Processes with Covariance Loss Boseon Yoo Jiwoo Lee Janghoon Ju Seijun Chung Soyeon Kim Jaesik Choi 171 15 0 01 Apr 2025
Deep Neural Nets as Hamiltonians Mike Winer Boris Hanin 465 0 0 31 Mar 2025
Towards Understanding the Optimization Mechanisms in Deep Learning Binchuan Qi Wei Gong Li Li 97 0 0 29 Mar 2025
ACE: A Cardinality Estimator for Set-Valued Queries Yufan Sheng Xin Cao Kaiqi Zhao Yixiang Fang Jianzhong Qi Wenjie Zhang Christian S. Jensen 101 0 0 19 Mar 2025
High-entropy Advantage in Neural Networks' Generalizability Entao Yang Wei Wei Yue Shang Ge Zhang AI4CE 123 0 0 17 Mar 2025
Contextual Similarity Distillation: Ensemble Uncertainties with a Single Model Moritz A. Zanger Pascal R. van der Vaart Wendelin Bohmer M. Spaan UQCV BDL 520 2 0 14 Mar 2025
How good is PAC-Bayes at explaining generalisation? Antoine Picard-Weibel Eugenio Clerico Roman Moscoviz Benjamin Guedj 96 0 0 11 Mar 2025
PIED: Physics-Informed Experimental Design for Inverse Problems Apivich Hemachandra Gregory Kang Ruey Lau Szu Hui Ng Bryan Kian Hsiang Low PINN 121 0 0 10 Mar 2025
Uncertainty Quantification From Scaling Laws in Deep Neural Networks Ibrahim Elsharkawy Yonatan Kahn Benjamin Hooberman UQCV 103 0 0 07 Mar 2025
Deep Learning is Not So Mysterious or Different Andrew Gordon Wilson 101 6 0 03 Mar 2025
Variational Bayesian Pseudo-Coreset Hyungi Lee Seanie Lee Juho Lee BDL 75 0 0 28 Feb 2025
Feature maps for the Laplacian kernel and its generalizations Sudhendu Ahir Parthe Pandit 105 0 0 24 Feb 2025
Generalized Kernel Inducing Points by Duality Gap for Dataset Distillation Tatsuya Aoyama Hanting Yang Hiroyuki Hanada Satoshi Akahane Tomonari Tanaka ... Noriaki Hashimoto Taro Murayama Hanju Lee Shinya Kojima Ichiro Takeuchi 159 0 0 18 Feb 2025
Student-t processes as infinite-width limits of posterior Bayesian neural networks Francesco Caporali Stefano Favaro Dario Trevisan BDL 482 0 0 06 Feb 2025
LoCA: Location-Aware Cosine Adaptation for Parameter-Efficient Fine-Tuning Zhekai Du Yinjie Min Jingjing Li Ke Lu Changliang Zou Liuhua Peng Tingjin Chu Mingming Gong 521 2 0 05 Feb 2025
Observation Noise and Initialization in Wide Neural Networks Sergio Calvo-Ordoñez Jonathan Plenk Richard Bergna Alvaro Cartea Jose Miguel Hernandez-Lobato Konstantina Palla Kamil Ciosek 130 1 0 03 Feb 2025
Uncertainty Quantification With Noise Injection in Neural Networks: A Bayesian Perspective Xueqiong Yuan Jipeng Li E. Kuruoglu UQCV BDL 155 0 0 21 Jan 2025
Issues with Neural Tangent Kernel Approach to Neural Networks Haoran Liu Anthony S. Tai David J. Crandall Chunfeng Huang 112 0 0 19 Jan 2025
Pareto Set Learning for Multi-Objective Reinforcement Learning Erlong Liu Yu-Chang Wu Xiaobin Huang Chengrui Gao Ren-Jian Wang Ke Xue Chao Qian OffRL 253 2 0 12 Jan 2025
Understanding How Nonlinear Layers Create Linearly Separable Features for Low-Dimensional Data Alec S. Xu Can Yaras Peng Wang Q. Qu 107 1 0 04 Jan 2025
Learning from Summarized Data: Gaussian Process Regression with Sample Quasi-Likelihood Yuta Shikuri GP 120 0 0 23 Dec 2024
Uncertainty separation via ensemble quantile regression Navid Ansari Hans-Peter Seidel Vahid Babaei UD UQCV 139 0 0 18 Dec 2024
Level-Set Parameters: Novel Representation for 3D Shape Analysis Huan Lei Hongdong Li Andreas Geiger Anthony Dick 154 0 0 18 Dec 2024
On the Ability of Deep Networks to Learn Symmetries from Data: A Neural Kernel Theory Andrea Perin Stéphane Deny 150 2 0 16 Dec 2024
Proportional infinite-width infinite-depth limit for deep linear neural networks Federico Bassetti Lucia Ladelli P. Rotondo 169 1 0 22 Nov 2024
Variational Bayesian Bow tie Neural Networks with Shrinkage Alisa Sheinkman Sara Wade BDL UQCV 111 0 0 17 Nov 2024
Inherently Interpretable and Uncertainty-Aware Models for Online Learning in Cyber-Security Problems Benjamin Kolicic Alberto Caron Chris Hicks V. Mavroudis AI4CE 94 0 0 14 Nov 2024
Understanding Representation of Deep Equilibrium Models from Neural Collapse Perspective Haixiang Sun Ye Shi 101 0 0 30 Oct 2024
On learning higher-order cumulants in diffusion models Gert Aarts Diaa E. Habibi Lei Wang K. Zhou 104 5 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 120 1 0 18 Oct 2024
Local transfer learning Gaussian process modeling, with applications to surrogate modeling of expensive computer simulators Xinming Wang Simon Mak John Joshua Miller Jianguo Wu 66 1 0 16 Oct 2024
Correspondence of NNGP Kernel and the Matern Kernel Amanda Muyskens Benjamin W. Priest I. Goumiri M. Schneider BDL 156 1 0 10 Oct 2024