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
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
Mining Explainable Predictive Features for Water Quality Management C. Muldoon Levent Gorgu J. O'Sullivan W. Meijer Gregory M. P. O'Hare FAtt 11 0 0 08 Dec 2022
Statistical Physics of Deep Neural Networks: Initialization toward Optimal Channels Kangyu Weng Aohua Cheng Ziyang Zhang Pei Sun Yang Tian 53 2 0 04 Dec 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 24 1 0 16 Nov 2022
Characterizing the Spectrum of the NTK via a Power Series Expansion Michael Murray Hui Jin Benjamin Bowman Guido Montúfar 38 11 0 15 Nov 2022
Overparameterized random feature regression with nearly orthogonal data Zhichao Wang Yizhe Zhu 29 3 0 11 Nov 2022
A Bayesian Semiparametric Method For Estimating Causal Quantile Effects Steven G. Xu Shu Yang Brian J. Reich CML 13 1 0 03 Nov 2022
Globally Gated Deep Linear Networks Qianyi Li H. Sompolinsky AI4CE 27 10 0 31 Oct 2022
A Solvable Model of Neural Scaling Laws A. Maloney Daniel A. Roberts J. Sully 47 51 0 30 Oct 2022
Proximal Mean Field Learning in Shallow Neural Networks Alexis M. H. Teter Iman Nodozi A. Halder FedML 43 1 0 25 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 24 5 0 23 Oct 2022
Efficient Dataset Distillation Using Random Feature Approximation Noel Loo Ramin Hasani Alexander Amini Daniela Rus DD 81 97 0 21 Oct 2022
Evolution of Neural Tangent Kernels under Benign and Adversarial Training Noel Loo Ramin Hasani Alexander Amini Daniela Rus AAML 36 13 0 21 Oct 2022
Meta-Principled Family of Hyperparameter Scaling Strategies Sho Yaida 58 16 0 10 Oct 2022
The Influence of Learning Rule on Representation Dynamics in Wide Neural Networks Blake Bordelon Cengiz Pehlevan 41 22 0 05 Oct 2022
On the infinite-depth limit of finite-width neural networks Soufiane Hayou 32 22 0 03 Oct 2022
Batch Bayesian optimisation via density-ratio estimation with guarantees Rafael Oliveira Louis C. Tiao Fabio Ramos 44 7 0 22 Sep 2022
Variational Inference for Infinitely Deep Neural Networks Achille Nazaret David M. Blei BDL 25 11 0 21 Sep 2022
Extrapolation and Spectral Bias of Neural Nets with Hadamard Product: a Polynomial Net Study Yongtao Wu Zhenyu Zhu Fanghui Liu Grigorios G. Chrysos V. Cevher 28 10 0 16 Sep 2022
Fast Neural Kernel Embeddings for General Activations Insu Han A. Zandieh Jaehoon Lee Roman Novak Lechao Xiao Amin Karbasi 65 18 0 09 Sep 2022
On Kernel Regression with Data-Dependent Kernels James B. Simon BDL 29 3 0 04 Sep 2022
Gaussian Process Surrogate Models for Neural Networks Michael Y. Li Erin Grant Thomas Griffiths BDL SyDa 38 7 0 11 Aug 2022
Deep Maxout Network Gaussian Process Libin Liang Ye Tian Ge Cheng BDL 14 0 0 08 Aug 2022
Single Model Uncertainty Estimation via Stochastic Data Centering Jayaraman J. Thiagarajan Rushil Anirudh V. Narayanaswamy P. Bremer UQCV OOD 32 26 0 14 Jul 2022
On the Robustness of Bayesian Neural Networks to Adversarial Attacks Luca Bortolussi Ginevra Carbone Luca Laurenti A. Patané G. Sanguinetti Matthew Wicker AAML 24 11 0 13 Jul 2022
Synergy and Symmetry in Deep Learning: Interactions between the Data, Model, and Inference Algorithm Lechao Xiao Jeffrey Pennington 42 10 0 11 Jul 2022
Memory Safe Computations with XLA Compiler A. Artemev Tilman Roeder Mark van der Wilk 29 8 0 28 Jun 2022
AutoInit: Automatic Initialization via Jacobian Tuning Tianyu He Darshil Doshi Andrey Gromov 19 4 0 27 Jun 2022
Making Look-Ahead Active Learning Strategies Feasible with Neural Tangent Kernels Mohamad Amin Mohamadi Wonho Bae Danica J. Sutherland 30 20 0 25 Jun 2022
A Fast, Well-Founded Approximation to the Empirical Neural Tangent Kernel Mohamad Amin Mohamadi Wonho Bae Danica J. Sutherland AAML 29 27 0 25 Jun 2022
Fast Finite Width Neural Tangent Kernel Roman Novak Jascha Narain Sohl-Dickstein S. Schoenholz AAML 28 54 0 17 Jun 2022
Large-width asymptotics for ReLU neural networks with $α$ -Stable initializations Stefano Favaro S. Fortini Stefano Peluchetti 20 2 0 16 Jun 2022
Wide Bayesian neural networks have a simple weight posterior: theory and accelerated sampling Jiri Hron Roman Novak Jeffrey Pennington Jascha Narain Sohl-Dickstein UQCV BDL 48 6 0 15 Jun 2022
Wavelet Regularization Benefits Adversarial Training Jun Yan Huilin Yin Xiaoyang Deng Zi-qin Zhao Wancheng Ge Hao Zhang Gerhard Rigoll AAML 19 2 0 08 Jun 2022
Asymptotic Properties for Bayesian Neural Network in Besov Space Kyeongwon Lee Jaeyong Lee BDL 19 4 0 01 Jun 2022
Optimal Activation Functions for the Random Features Regression Model Jianxin Wang José Bento 37 3 0 31 May 2022
Why So Pessimistic? Estimating Uncertainties for Offline RL through Ensembles, and Why Their Independence Matters Seyed Kamyar Seyed Ghasemipour S. Gu Ofir Nachum OffRL 31 69 0 27 May 2022
On Bridging the Gap between Mean Field and Finite Width in Deep Random Neural Networks with Batch Normalization Amir Joudaki Hadi Daneshmand Francis R. Bach AI4CE 21 2 0 25 May 2022
Gaussian Pre-Activations in Neural Networks: Myth or Reality? Pierre Wolinski Julyan Arbel AI4CE 76 8 0 24 May 2022
Self-Consistent Dynamical Field Theory of Kernel Evolution in Wide Neural Networks Blake Bordelon Cengiz Pehlevan MLT 40 77 0 19 May 2022
Deep neural networks with dependent weights: Gaussian Process mixture limit, heavy tails, sparsity and compressibility Hoileong Lee Fadhel Ayed Paul Jung Juho Lee Hongseok Yang François Caron 46 10 0 17 May 2022
Incorporating Prior Knowledge into Neural Networks through an Implicit Composite Kernel Ziyang Jiang Tongshu Zheng Yiling Liu David Carlson 30 4 0 15 May 2022
Generalized Variational Inference in Function Spaces: Gaussian Measures meet Bayesian Deep Learning Veit Wild Robert Hu Dino Sejdinovic BDL 51 11 0 12 May 2022
Investigating Generalization by Controlling Normalized Margin Alexander R. Farhang Jeremy Bernstein Kushal Tirumala Yang Liu Yisong Yue 31 6 0 08 May 2022
NeuralEF: Deconstructing Kernels by Deep Neural Networks Zhijie Deng Jiaxin Shi Jun Zhu 27 18 0 30 Apr 2022
Convergence of neural networks to Gaussian mixture distribution Yasuhiko Asao Ryotaro Sakamoto S. Takagi BDL 35 2 0 26 Apr 2022
Polynomial-time Sparse Measure Recovery: From Mean Field Theory to Algorithm Design Hadi Daneshmand Francis R. Bach 15 1 0 16 Apr 2022
Towards a Unified Framework for Uncertainty-aware Nonlinear Variable Selection with Theoretical Guarantees Wenying Deng Beau Coker Rajarshi Mukherjee J. Liu B. Coull 19 2 0 15 Apr 2022
Single-level Adversarial Data Synthesis based on Neural Tangent Kernels Yu-Rong Zhang Ruei-Yang Su Sheng-Yen Chou Shan Wu GAN 15 2 0 08 Apr 2022
Bayesian Deep Learning with Multilevel Trace-class Neural Networks Neil K. Chada Ajay Jasra K. Law Sumeetpal S. Singh BDL UQCV 83 3 0 24 Mar 2022