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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
Predicting Training Time Without Training Luca Zancato Alessandro Achille Avinash Ravichandran Rahul Bhotika Stefano Soatto 156 24 0 28 Aug 2020
A Dynamical Central Limit Theorem for Shallow Neural Networks Zhengdao Chen Grant M. Rotskoff Joan Bruna Eric Vanden-Eijnden 96 30 0 21 Aug 2020
Asymptotics of Wide Convolutional Neural Networks Anders Andreassen Ethan Dyer 76 23 0 19 Aug 2020
Neural Networks and Quantum Field Theory James Halverson Anindita Maiti Keegan Stoner 119 78 0 19 Aug 2020
Adaptive Signal Variances: CNN Initialization Through Modern Architectures Takahiko Henmi E. R. R. Zara Yoshihiro Hirohashi Tsuyoshi Kato 88 2 0 16 Aug 2020
The Neural Tangent Kernel in High Dimensions: Triple Descent and a Multi-Scale Theory of Generalization Ben Adlam Jeffrey Pennington 68 125 0 15 Aug 2020
Stochastic Bayesian Neural Networks Abhinav Sagar BDL UQCV 68 0 0 12 Aug 2020
Shallow Univariate ReLu Networks as Splines: Initialization, Loss Surface, Hessian, & Gradient Flow Dynamics Justin Sahs Ryan Pyle Aneel Damaraju J. O. Caro Onur Tavaslioglu Andy Lu Ankit B. Patel 65 19 0 04 Aug 2020
Cold Posteriors and Aleatoric Uncertainty Ben Adlam Jasper Snoek Samuel L. Smith BDL UQCV 105 24 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 118 214 0 31 Jul 2020
When and why PINNs fail to train: A neural tangent kernel perspective Sizhuang He Xinling Yu P. Perdikaris 148 932 0 28 Jul 2020
DeepKriging: Spatially Dependent Deep Neural Networks for Spatial Prediction Wanfang Chen Yuxiao Li Brian J. Reich Ying Sun 111 33 0 23 Jul 2020
Disentangling the Gauss-Newton Method and Approximate Inference for Neural Networks Alexander Immer BDL 51 4 0 21 Jul 2020
Early Stopping in Deep Networks: Double Descent and How to Eliminate it Reinhard Heckel Fatih Yilmaz 96 45 0 20 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 38 0 0 15 Jul 2020
Structured Weight Priors for Convolutional Neural Networks Tim Pearce Andrew Y. K. Foong Alexandra Brintrup BDL 108 2 0 12 Jul 2020
Bayesian Deep Ensembles via the Neural Tangent Kernel Bobby He Balaji Lakshminarayanan Yee Whye Teh BDL UQCV 84 121 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 50 6 0 10 Jul 2020
Bayesian Neural Networks for Fast SUSY Predictions B. Kronheim M. Kuchera Harrison B. Prosper A. Karbo 60 17 0 09 Jul 2020
Doubly infinite residual neural networks: a diffusion process approach Stefano Peluchetti Stefano Favaro 48 2 0 07 Jul 2020
Parametric machines: a fresh approach to architecture search Pietro Vertechi M. Bergomi 93 2 0 06 Jul 2020
Qualitative Analysis of Monte Carlo Dropout Ronald Seoh UQCV BDL 54 29 0 03 Jul 2020
On the Similarity between the Laplace and Neural Tangent Kernels Amnon Geifman A. Yadav Yoni Kasten Meirav Galun David Jacobs Ronen Basri 172 96 0 03 Jul 2020
A Chain Graph Interpretation of Real-World Neural Networks Yuesong Shen Zorah Lähner GNN AI4CE 38 0 0 30 Jun 2020
Associative Memory in Iterated Overparameterized Sigmoid Autoencoders Yibo Jiang Cengiz Pehlevan 72 14 0 30 Jun 2020
Uniform Priors for Data-Efficient Transfer Samarth Sinha Karsten Roth Anirudh Goyal Marzyeh Ghassemi Hugo Larochelle Animesh Garg OOD 135 0 0 30 Jun 2020
Is SGD a Bayesian sampler? Well, almost Chris Mingard Guillermo Valle Pérez Joar Skalse A. Louis BDL 90 53 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 126 107 0 25 Jun 2020
Tensor Programs II: Neural Tangent Kernel for Any Architecture Greg Yang 156 139 0 25 Jun 2020
When Do Neural Networks Outperform Kernel Methods? Behrooz Ghorbani Song Mei Theodor Misiakiewicz Andrea Montanari 143 189 0 24 Jun 2020
Likelihood-Free Gaussian Process for Regression Yuta Shikuri 50 0 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 205 190 0 23 Jun 2020
Bayesian Neural Networks: An Introduction and Survey Ethan Goan Clinton Fookes BDL UQCV 94 211 0 22 Jun 2020
Exact posterior distributions of wide Bayesian neural networks Jiri Hron Yasaman Bahri Roman Novak Jeffrey Pennington Jascha Narain Sohl-Dickstein UQCV BDL 115 28 0 18 Jun 2020
Infinite attention: NNGP and NTK for deep attention networks Jiri Hron Yasaman Bahri Jascha Narain Sohl-Dickstein Roman Novak 68 116 0 18 Jun 2020
The Recurrent Neural Tangent Kernel Sina Alemohammad Zichao Wang Randall Balestriero Richard Baraniuk AAML 111 78 0 18 Jun 2020
On the Preservation of Spatio-temporal Information in Machine Learning Applications Yigit Oktar Mehmet Türkan 65 1 0 15 Jun 2020
NP-PROV: Neural Processes with Position-Relevant-Only Variances Xuesong Wang Lina Yao Xianzhi Wang Feiping Nie BDL 71 3 0 15 Jun 2020
Sample complexity and effective dimension for regression on manifolds Andrew D. McRae Justin Romberg Mark A. Davenport 119 8 0 13 Jun 2020
On the asymptotics of wide networks with polynomial activations Kyle Aitken Guy Gur-Ari 65 23 0 11 Jun 2020
Coresets via Bilevel Optimization for Continual Learning and Streaming Zalan Borsos Mojmír Mutný Andreas Krause CLL 115 241 0 06 Jun 2020
Learning across label confidence distributions using Filtered Transfer Learning S. Tonekaboni Andrew E. Brereton Z. Safikhani A. Windemuth B. Haibe-Kains S. MacKinnon FedML 45 2 0 03 Jun 2020
Spectra of the Conjugate Kernel and Neural Tangent Kernel for linear-width neural networks Z. Fan Zhichao Wang 127 74 0 25 May 2020
Deep covariate-learning: optimising information extraction from terrain texture for geostatistical modelling applications Charlie Kirkwood 46 4 0 22 May 2020
Deep Latent-Variable Kernel Learning Haitao Liu Yew-Soon Ong Xiaomo Jiang Xiaofang Wang BDL 59 8 0 18 May 2020
Global inducing point variational posteriors for Bayesian neural networks and deep Gaussian processes Sebastian W. Ober Laurence Aitchison BDL 116 60 0 17 May 2020
Modularizing Deep Learning via Pairwise Learning With Kernels Shiyu Duan Shujian Yu José C. Príncipe MoMe 83 20 0 12 May 2020
Provable Training of a ReLU Gate with an Iterative Non-Gradient Algorithm Sayar Karmakar Anirbit Mukherjee 79 7 0 08 May 2020
Random Features for Kernel Approximation: A Survey on Algorithms, Theory, and Beyond Fanghui Liu Xiaolin Huang Yudong Chen Johan A. K. Suykens BDL 169 177 0 23 Apr 2020
Space of Functions Computed by Deep-Layered Machines Alexander Mozeika Bo Li D. Saad 90 8 0 19 Apr 2020