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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
Wider Networks Learn Better Features D. Gilboa Guy Gur-Ari 59 7 0 25 Sep 2019
Neural networks are a priori biased towards Boolean functions with low entropy Chris Mingard Joar Skalse Guillermo Valle Pérez David Martínez-Rubio Vladimir Mikulik A. Louis FAtt AI4CE 113 39 0 25 Sep 2019
Asymptotics of Wide Networks from Feynman Diagrams Ethan Dyer Guy Gur-Ari 120 115 0 25 Sep 2019
PAC-Bayesian Bounds for Deep Gaussian Processes R. Foll Ingo Steinwart BDL 44 1 0 22 Sep 2019
Adversarial Vulnerability Bounds for Gaussian Process Classification M. Smith Kathrin Grosse Michael Backes Mauricio A. Alvarez AAML 60 9 0 19 Sep 2019
Deep kernel learning for integral measurements Carl Jidling J. Hendriks Thomas B. Schon A. Wills 78 7 0 04 Sep 2019
Neural Policy Gradient Methods: Global Optimality and Rates of Convergence Lingxiao Wang Qi Cai Zhuoran Yang Zhaoran Wang 121 242 0 29 Aug 2019
Deep Learning Theory Review: An Optimal Control and Dynamical Systems Perspective Guan-Horng Liu Evangelos A. Theodorou AI4CE 125 72 0 28 Aug 2019
Finite size corrections for neural network Gaussian processes J. Antognini BDL 89 31 0 27 Aug 2019
Effect of Activation Functions on the Training of Overparametrized Neural Nets A. Panigrahi Abhishek Shetty Navin Goyal 92 21 0 16 Aug 2019
The generalization error of random features regression: Precise asymptotics and double descent curve Song Mei Andrea Montanari 197 640 0 14 Aug 2019
A Fine-Grained Spectral Perspective on Neural Networks Greg Yang Hadi Salman 144 113 0 24 Jul 2019
Mitigating Uncertainty in Document Classification Xuchao Zhang Fanglan Chen Chang-Tien Lu Naren Ramakrishnan 64 43 0 17 Jul 2019
Sequential online prediction in the presence of outliers and change points: an instant temporal structure learning approach Bin Liu Yu Qi Ke-Jia Chen AI4TS 43 11 0 15 Jul 2019
Order and Chaos: NTK views on DNN Normalization, Checkerboard and Boundary Artifacts Arthur Jacot Franck Gabriel François Ged Clément Hongler 79 24 0 11 Jul 2019
Ín-Between' Uncertainty in Bayesian Neural Networks Andrew Y. K. Foong Yingzhen Li José Miguel Hernández-Lobato Richard Turner BDL UQCV 80 121 0 27 Jun 2019
Model Bridging: Connection between Simulation Model and Neural Network Keiichi Kisamori Keisuke Yamazaki Yuto Komori Hiroshi Tokieda 74 1 0 22 Jun 2019
Disentangling feature and lazy training in deep neural networks Mario Geiger S. Spigler Arthur Jacot Matthieu Wyart 141 17 0 19 Jun 2019
Learning Curves for Deep Neural Networks: A Gaussian Field Theory Perspective Omry Cohen Orit Malka Zohar Ringel AI4CE 89 22 0 12 Jun 2019
The Normalization Method for Alleviating Pathological Sharpness in Wide Neural Networks Ryo Karakida S. Akaho S. Amari 75 41 0 07 Jun 2019
Approximate Inference Turns Deep Networks into Gaussian Processes Mohammad Emtiyaz Khan Alexander Immer Ehsan Abedi M. Korzepa UQCV BDL 142 125 0 05 Jun 2019
Deep ReLU Networks Have Surprisingly Few Activation Patterns Boris Hanin David Rolnick 138 229 0 03 Jun 2019
A Mean Field Theory of Quantized Deep Networks: The Quantization-Depth Trade-Off Yaniv Blumenfeld D. Gilboa Daniel Soudry MQ 91 14 0 03 Jun 2019
Quantifying Point-Prediction Uncertainty in Neural Networks via Residual Estimation with an I/O Kernel Xin Qiu Elliot Meyerson Risto Miikkulainen UQCV 118 54 0 03 Jun 2019
On the Inductive Bias of Neural Tangent Kernels A. Bietti Julien Mairal 148 260 0 29 May 2019
Implicit Rugosity Regularization via Data Augmentation Daniel LeJeune Randall Balestriero Hamid Javadi Richard G. Baraniuk 83 4 0 28 May 2019
Infinitely deep neural networks as diffusion processes Stefano Peluchetti Stefano Favaro ODL 105 32 0 27 May 2019
Scalable Training of Inference Networks for Gaussian-Process Models Jiaxin Shi Mohammad Emtiyaz Khan Jun Zhu BDL 67 18 0 27 May 2019
Interpretable deep Gaussian processes with moments Chi-Ken Lu Scott Cheng-Hsin Yang Xiaoran Hao Patrick Shafto 91 19 0 27 May 2019
Learning spectrograms with convolutional spectral kernels Zheyan Shen Markus Heinonen Samuel Kaski 64 9 0 23 May 2019
Expressive Priors in Bayesian Neural Networks: Kernel Combinations and Periodic Functions Tim Pearce Russell Tsuchida Mohamed H. Zaki Alexandra Brintrup A. Neely BDL 79 50 0 15 May 2019
Sub-Weibull distributions: generalizing sub-Gaussian and sub-Exponential properties to heavier-tailed distributions M. Vladimirova Stéphane Girard Hien Nguyen Julyan Arbel 119 92 0 13 May 2019
The Effect of Network Width on Stochastic Gradient Descent and Generalization: an Empirical Study Daniel S. Park Jascha Narain Sohl-Dickstein Quoc V. Le Samuel L. Smith 107 57 0 09 May 2019
Similarity of Neural Network Representations Revisited Simon Kornblith Mohammad Norouzi Honglak Lee Geoffrey E. Hinton 196 1,442 0 01 May 2019
LS-SVR as a Bayesian RBF network Diego Mesquita Luis A. Freitas Joao P. P. Gomes C. L. C. Mattos 66 12 0 01 May 2019
On Exact Computation with an Infinitely Wide Neural Net Sanjeev Arora S. Du Wei Hu Zhiyuan Li Ruslan Salakhutdinov Ruosong Wang 332 929 0 26 Apr 2019
Linear Multiple Low-Rank Kernel Based Stationary Gaussian Processes Regression for Time Series Feng Yin Lishuo Pan Xinwei He Tianshi Chen Sergios Theodoridis Zhi-Quan Zhi-Quan Luo AI4TS 55 26 0 21 Apr 2019
A Bayesian Perspective on the Deep Image Prior Zezhou Cheng Matheus Gadelha Subhransu Maji Daniel Sheldon BDL UQCV 81 137 0 16 Apr 2019
Nearest-Neighbor Neural Networks for Geostatistics Haoyu Wang Yawen Guan Brian J. Reich BDL 57 16 0 28 Mar 2019
Functional Variational Bayesian Neural Networks Shengyang Sun Guodong Zhang Jiaxin Shi Roger C. Grosse BDL 96 240 0 14 Mar 2019
Implicit Regularization in Over-parameterized Neural Networks M. Kubo Ryotaro Banno Hidetaka Manabe Masataka Minoji 90 23 0 05 Mar 2019
Deeper Connections between Neural Networks and Gaussian Processes Speed-up Active Learning Evgenii Tsymbalov Sergei Makarychev Alexander Shapeev Maxim Panov BDL UQCV 52 21 0 27 Feb 2019
Function Space Particle Optimization for Bayesian Neural Networks Ziyu Wang Zhaolin Ren Jun Zhu Bo Zhang BDL 77 65 0 26 Feb 2019
A Mean Field Theory of Batch Normalization Greg Yang Jeffrey Pennington Vinay Rao Jascha Narain Sohl-Dickstein S. Schoenholz 104 180 0 21 Feb 2019
On the Impact of the Activation Function on Deep Neural Networks Training Soufiane Hayou Arnaud Doucet Judith Rousseau ODL 81 201 0 19 Feb 2019
Wide Neural Networks of Any Depth Evolve as Linear Models Under Gradient Descent Jaehoon Lee Lechao Xiao S. Schoenholz Yasaman Bahri Roman Novak Jascha Narain Sohl-Dickstein Jeffrey Pennington 250 1,112 0 18 Feb 2019
Bayesian Image Classification with Deep Convolutional Gaussian Processes Vincent Dutordoir Mark van der Wilk A. Artemev J. Hensman UQCV BDL 161 32 0 15 Feb 2019
Scaling Limits of Wide Neural Networks with Weight Sharing: Gaussian Process Behavior, Gradient Independence, and Neural Tangent Kernel Derivation Greg Yang 243 289 0 13 Feb 2019
Mean Field Limit of the Learning Dynamics of Multilayer Neural Networks Phan-Minh Nguyen AI4CE 97 72 0 07 Feb 2019
The role of a layer in deep neural networks: a Gaussian Process perspective Oded Ben-David Zohar Ringel AI4CE 44 3 0 06 Feb 2019