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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A connection between probability, physics and neural networks Sascha Ranftl PINN 22 9 0 26 Sep 2022
Variational Inference for Infinitely Deep Neural Networks Achille Nazaret David M. Blei BDL 27 11 0 21 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 31 3 0 04 Sep 2022
Neural Tangent Kernel: A Survey Eugene Golikov Eduard Pokonechnyy Vladimir Korviakov 40 13 0 29 Aug 2022
Bayesian Neural Network Language Modeling for Speech Recognition Boyang Xue Shoukang Hu Junhao Xu Mengzhe Geng Xunying Liu Helen M. Meng UQCV BDL 49 14 0 28 Aug 2022
Gaussian Process Surrogate Models for Neural Networks Michael Y. Li Erin Grant Thomas Griffiths BDL SyDa 43 7 0 11 Aug 2022
Deep Maxout Network Gaussian Process Libin Liang Ye Tian Ge Cheng BDL 19 0 0 08 Aug 2022
Multi-fidelity surrogate modeling using long short-term memory networks Paolo Conti Mengwu Guo Andrea Manzoni J. Hesthaven AI4CE 36 48 0 05 Aug 2022
What Can Be Learnt With Wide Convolutional Neural Networks? Francesco Cagnetta Alessandro Favero Matthieu Wyart MLT 46 12 0 01 Aug 2022
Gradient-based Bi-level Optimization for Deep Learning: A Survey Can Chen Xiangshan Chen Chen Ma Zixuan Liu Xue Liu 98 36 0 24 Jul 2022
Statistical Hypothesis Testing Based on Machine Learning: Large Deviations Analysis P. Braca L. Millefiori A. Aubry S. Maranò A. De Maio P. Willett 39 12 0 22 Jul 2022
Single Model Uncertainty Estimation via Stochastic Data Centering Jayaraman J. Thiagarajan Rushil Anirudh V. Narayanaswamy P. Bremer UQCV OOD 35 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 45 10 0 11 Jul 2022
Variational Neural Networks Illia Oleksiienko D. Tran Alexandros Iosifidis BDL UQCV 41 8 0 04 Jul 2022
Memory Safe Computations with XLA Compiler A. Artemev Tilman Roeder Mark van der Wilk 37 8 0 28 Jun 2022
AutoInit: Automatic Initialization via Jacobian Tuning Tianyu He Darshil Doshi Andrey Gromov 27 4 0 27 Jun 2022
Distributional Gaussian Processes Layers for Out-of-Distribution Detection S. Popescu D. Sharp James H. Cole Konstantinos Kamnitsas Ben Glocker OOD 34 0 0 27 Jun 2022
A Fast, Well-Founded Approximation to the Empirical Neural Tangent Kernel Mohamad Amin Mohamadi Wonho Bae Danica J. Sutherland AAML 34 27 0 25 Jun 2022
Laziness, Barren Plateau, and Noise in Machine Learning Junyu Liu Zexi Lin Liang Jiang 43 21 0 19 Jun 2022
Photoelectric Factor Prediction Using Automated Learning and Uncertainty Quantification K. Alsamadony A. Ibrahim S. Elkatatny A. Abdulraheem 17 1 0 17 Jun 2022
Fast Finite Width Neural Tangent Kernel Roman Novak Jascha Narain Sohl-Dickstein S. Schoenholz AAML 30 54 0 17 Jun 2022
Large-width asymptotics for ReLU neural networks with $α$ -Stable initializations Stefano Favaro S. Fortini Stefano Peluchetti 28 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
Implicit Regularization or Implicit Conditioning? Exact Risk Trajectories of SGD in High Dimensions Courtney Paquette Elliot Paquette Ben Adlam Jeffrey Pennington 25 13 0 15 Jun 2022
Deep Variational Implicit Processes Luis A. Ortega Simón Rodríguez Santana Daniel Hernández-Lobato BDL 33 5 0 14 Jun 2022
Gradient Boosting Performs Gaussian Process Inference Aleksei Ustimenko Artem Beliakov Liudmila Prokhorenkova BDL 28 5 0 11 Jun 2022
Overcoming the Spectral Bias of Neural Value Approximation Ge Yang Anurag Ajay Pulkit Agrawal 39 25 0 09 Jun 2022
Adversarial Reprogramming Revisited Matthias Englert R. Lazic AAML 29 9 0 07 Jun 2022
The Neural Covariance SDE: Shaped Infinite Depth-and-Width Networks at Initialization Mufan Li Mihai Nica Daniel M. Roy 55 37 0 06 Jun 2022
Asymptotic Properties for Bayesian Neural Network in Besov Space Kyeongwon Lee Jaeyong Lee BDL 27 4 0 01 Jun 2022
Rethinking Bayesian Learning for Data Analysis: The Art of Prior and Inference in Sparsity-Aware Modeling Lei Cheng Feng Yin Sergios Theodoridis S. Chatzis Tsung-Hui Chang 73 75 0 28 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
Position: Tensor Networks are a Valuable Asset for Green AI Eva Memmel Clara Menzen Jetze T. Schuurmans Frederiek Wesel Kim Batselier 38 6 0 25 May 2022
Gaussian Pre-Activations in Neural Networks: Myth or Reality? Pierre Wolinski Julyan Arbel AI4CE 76 8 0 24 May 2022
Split personalities in Bayesian Neural Networks: the case for full marginalisation David Yallup Will Handley Michael P. Hobson A. Lasenby Pablo Lemos 30 1 0 23 May 2022
Mean-Field Analysis of Two-Layer Neural Networks: Global Optimality with Linear Convergence Rates Jingwei Zhang Xunpeng Huang Jincheng Yu MLT 18 1 0 19 May 2022
Diverse Weight Averaging for Out-of-Distribution Generalization Alexandre Ramé Matthieu Kirchmeyer Thibaud Rahier A. Rakotomamonjy Patrick Gallinari Matthieu Cord OOD 199 129 0 19 May 2022
Self-Consistent Dynamical Field Theory of Kernel Evolution in Wide Neural Networks Blake Bordelon Cengiz Pehlevan MLT 45 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 51 10 0 17 May 2022
Incorporating Prior Knowledge into Neural Networks through an Implicit Composite Kernel Ziyang Jiang Tongshu Zheng Yiling Liu David Carlson 32 4 0 15 May 2022
Sobolev Acceleration and Statistical Optimality for Learning Elliptic Equations via Gradient Descent Yiping Lu Jose H. Blanchet Lexing Ying 40 7 0 15 May 2022
Deep Architecture Connectivity Matters for Its Convergence: A Fine-Grained Analysis Wuyang Chen Wei Huang Xinyu Gong Boris Hanin Zhangyang Wang 43 7 0 11 May 2022
Investigating Generalization by Controlling Normalized Margin Alexander R. Farhang Jeremy Bernstein Kushal Tirumala Yang Liu Yisong Yue 33 6 0 08 May 2022
Variational Inference for Nonlinear Inverse Problems via Neural Net Kernels: Comparison to Bayesian Neural Networks, Application to Topology Optimization Vahid Keshavarzzadeh Robert M. Kirby A. Narayan BDL 24 2 0 07 May 2022
NeuralEF: Deconstructing Kernels by Deep Neural Networks Zhijie Deng Jiaxin Shi Jun Zhu 32 18 0 30 Apr 2022
Deep Ensemble as a Gaussian Process Approximate Posterior Zhijie Deng Feng Zhou Jianfei Chen Guoqiang Wu Jun Zhu UQCV 24 5 0 30 Apr 2022
Convergence of neural networks to Gaussian mixture distribution Yasuhiko Asao Ryotaro Sakamoto S. Takagi BDL 40 2 0 26 Apr 2022
On Feature Learning in Neural Networks with Global Convergence Guarantees Zhengdao Chen Eric Vanden-Eijnden Joan Bruna MLT 36 13 0 22 Apr 2022