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
On Random Matrices Arising in Deep Neural Networks: General I.I.D. Case L. Pastur V. Slavin CML 24 12 0 20 Nov 2020
Towards NNGP-guided Neural Architecture Search Daniel S. Park Jaehoon Lee Daiyi Peng Yuan Cao Jascha Narain Sohl-Dickstein BDL 26 33 0 11 Nov 2020
Kernel Dependence Network Chieh-Tsai Wu A. Masoomi Arthur Gretton Jennifer Dy 16 0 0 04 Nov 2020
Which Minimizer Does My Neural Network Converge To? Manuel Nonnenmacher David Reeb Ingo Steinwart ODL 8 4 0 04 Nov 2020
Dataset Meta-Learning from Kernel Ridge-Regression Timothy Nguyen Zhourung Chen Jaehoon Lee DD 36 240 0 30 Oct 2020
Do Wide and Deep Networks Learn the Same Things? Uncovering How Neural Network Representations Vary with Width and Depth Thao Nguyen M. Raghu Simon Kornblith OOD 13 264 0 29 Oct 2020
A Bayesian Perspective on Training Speed and Model Selection Clare Lyle Lisa Schut Binxin Ru Y. Gal Mark van der Wilk 44 24 0 27 Oct 2020
A Probabilistic Representation of Deep Learning for Improving The Information Theoretic Interpretability Xinjie Lan Kenneth Barner FAtt 19 2 0 27 Oct 2020
Stable ResNet Soufiane Hayou Eugenio Clerico Bo He George Deligiannidis Arnaud Doucet Judith Rousseau ODL SSeg 46 51 0 24 Oct 2020
Label-Aware Neural Tangent Kernel: Toward Better Generalization and Local Elasticity Shuxiao Chen Hangfeng He Weijie J. Su 12 23 0 22 Oct 2020
Probabilistic Numeric Convolutional Neural Networks Marc Finzi Roberto Bondesan Max Welling BDL AI4TS 29 13 0 21 Oct 2020
Stationary Activations for Uncertainty Calibration in Deep Learning Lassi Meronen Christabella Irwanto Arno Solin UQCV BDL 14 18 0 19 Oct 2020
The Ridgelet Prior: A Covariance Function Approach to Prior Specification for Bayesian Neural Networks Takuo Matsubara Chris J. Oates F. Briol BDL UQCV 21 17 0 16 Oct 2020
Exploring the Uncertainty Properties of Neural Networks' Implicit Priors in the Infinite-Width Limit Ben Adlam Jaehoon Lee Lechao Xiao Jeffrey Pennington Jasper Snoek UQCV BDL 28 15 0 14 Oct 2020
Machine Learning Force Fields Oliver T. Unke Stefan Chmiela H. E. Sauceda M. Gastegger I. Poltavsky Kristof T. Schütt A. Tkatchenko K. Müller AI4CE 34 888 0 14 Oct 2020
Deep kernel processes Laurence Aitchison Adam X. Yang Sebastian W. Ober BDL 24 41 0 04 Oct 2020
Deep Equals Shallow for ReLU Networks in Kernel Regimes A. Bietti Francis R. Bach 30 86 0 30 Sep 2020
Improving Query Efficiency of Black-box Adversarial Attack Yang Bai Yuyuan Zeng Yong Jiang Yisen Wang Shutao Xia Weiwei Guo AAML MLAU 37 52 0 24 Sep 2020
Tensor Programs III: Neural Matrix Laws Greg Yang 19 44 0 22 Sep 2020
InClass Nets: Independent Classifier Networks for Nonparametric Estimation of Conditional Independence Mixture Models and Unsupervised Classification Konstantin T. Matchev Prasanth Shyamsundar CML 11 0 0 31 Aug 2020
Asymptotics of Wide Convolutional Neural Networks Anders Andreassen Ethan Dyer 22 23 0 19 Aug 2020
Neural Networks and Quantum Field Theory James Halverson Anindita Maiti Keegan Stoner 26 76 0 19 Aug 2020
The Neural Tangent Kernel in High Dimensions: Triple Descent and a Multi-Scale Theory of Generalization Ben Adlam Jeffrey Pennington 23 124 0 15 Aug 2020
Benign Overfitting and Noisy Features Zhu Li Weijie Su Dino Sejdinovic 10 22 0 06 Aug 2020
Cold Posteriors and Aleatoric Uncertainty Ben Adlam Jasper Snoek Samuel L. Smith BDL UQCV 26 23 0 31 Jul 2020
Finite Versus Infinite Neural Networks: an Empirical Study Jaehoon Lee S. Schoenholz Jeffrey Pennington Ben Adlam Lechao Xiao Roman Novak Jascha Narain Sohl-Dickstein 28 208 0 31 Jul 2020
When and why PINNs fail to train: A neural tangent kernel perspective Sizhuang He Xinling Yu P. Perdikaris 33 880 0 28 Jul 2020
From deep to Shallow: Equivalent Forms of Deep Networks in Reproducing Kernel Krein Space and Indefinite Support Vector Machines A. Shilton Sunil Gupta Santu Rana Svetha Venkatesh 19 0 0 15 Jul 2020
Bayesian Deep Ensembles via the Neural Tangent Kernel Bobby He Balaji Lakshminarayanan Yee Whye Teh BDL UQCV 14 116 0 11 Jul 2020
Characteristics of Monte Carlo Dropout in Wide Neural Networks Joachim Sicking Maram Akila Tim Wirtz Sebastian Houben Asja Fischer BDL UQCV 12 6 0 10 Jul 2020
Doubly infinite residual neural networks: a diffusion process approach Stefano Peluchetti Stefano Favaro 14 2 0 07 Jul 2020
On the Similarity between the Laplace and Neural Tangent Kernels Amnon Geifman A. Yadav Yoni Kasten Meirav Galun David Jacobs Ronen Basri 23 89 0 03 Jul 2020
Beyond Signal Propagation: Is Feature Diversity Necessary in Deep Neural Network Initialization? Yaniv Blumenfeld D. Gilboa Daniel Soudry ODL 30 13 0 02 Jul 2020
Associative Memory in Iterated Overparameterized Sigmoid Autoencoders Yibo Jiang Cengiz Pehlevan 19 13 0 30 Jun 2020
Uniform Priors for Data-Efficient Transfer Samarth Sinha Karsten Roth Anirudh Goyal Marzyeh Ghassemi Hugo Larochelle Animesh Garg OOD 26 0 0 30 Jun 2020
Is SGD a Bayesian sampler? Well, almost Chris Mingard Guillermo Valle Pérez Joar Skalse A. Louis BDL 23 51 0 26 Jun 2020
The Gaussian equivalence of generative models for learning with shallow neural networks Sebastian Goldt Bruno Loureiro Galen Reeves Florent Krzakala M. Mézard Lenka Zdeborová BDL 41 100 0 25 Jun 2020
Tensor Programs II: Neural Tangent Kernel for Any Architecture Greg Yang 58 135 0 25 Jun 2020
When Do Neural Networks Outperform Kernel Methods? Behrooz Ghorbani Song Mei Theodor Misiakiewicz Andrea Montanari 29 185 0 24 Jun 2020
Spectral Bias and Task-Model Alignment Explain Generalization in Kernel Regression and Infinitely Wide Neural Networks Abdulkadir Canatar Blake Bordelon Cengiz Pehlevan 27 181 0 23 Jun 2020
Exact posterior distributions of wide Bayesian neural networks Jiri Hron Yasaman Bahri Roman Novak Jeffrey Pennington Jascha Narain Sohl-Dickstein UQCV BDL 23 27 0 18 Jun 2020
Infinite attention: NNGP and NTK for deep attention networks Jiri Hron Yasaman Bahri Jascha Narain Sohl-Dickstein Roman Novak 16 113 0 18 Jun 2020
Depth Uncertainty in Neural Networks Javier Antorán J. Allingham José Miguel Hernández-Lobato UQCV OOD BDL 41 100 0 15 Jun 2020
Spectra of the Conjugate Kernel and Neural Tangent Kernel for linear-width neural networks Z. Fan Zhichao Wang 44 71 0 25 May 2020
Deep Latent-Variable Kernel Learning Haitao Liu Yew-Soon Ong Xiaomo Jiang Xiaofang Wang BDL 22 8 0 18 May 2020
Global inducing point variational posteriors for Bayesian neural networks and deep Gaussian processes Sebastian W. Ober Laurence Aitchison BDL 26 60 0 17 May 2020
Adversarial Robustness Guarantees for Random Deep Neural Networks Giacomo De Palma B. Kiani S. Lloyd AAML OOD 21 8 0 13 Apr 2020
On the Neural Tangent Kernel of Deep Networks with Orthogonal Initialization Wei Huang Weitao Du R. Xu 6 37 0 13 Apr 2020
Reinforcement Learning via Gaussian Processes with Neural Network Dual Kernels I. Goumiri Benjamin W. Priest M. Schneider GP BDL 6 6 0 10 Apr 2020
Predicting the outputs of finite deep neural networks trained with noisy gradients Gadi Naveh Oded Ben-David H. Sompolinsky Zohar Ringel 19 21 0 02 Apr 2020