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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Deep kernel learning for integral measurements Carl Jidling J. Hendriks Thomas B. Schon A. Wills 45 7 0 04 Sep 2019
Neural Policy Gradient Methods: Global Optimality and Rates of Convergence Lingxiao Wang Qi Cai Zhuoran Yang Zhaoran Wang 25 236 0 29 Aug 2019
Deep Learning Theory Review: An Optimal Control and Dynamical Systems Perspective Guan-Horng Liu Evangelos A. Theodorou AI4CE 32 71 0 28 Aug 2019
Finite size corrections for neural network Gaussian processes J. Antognini BDL 30 30 0 27 Aug 2019
Effect of Activation Functions on the Training of Overparametrized Neural Nets A. Panigrahi Abhishek Shetty Navin Goyal 19 20 0 16 Aug 2019
The generalization error of random features regression: Precise asymptotics and double descent curve Song Mei Andrea Montanari 62 629 0 14 Aug 2019
A Fine-Grained Spectral Perspective on Neural Networks Greg Yang Hadi Salman 35 111 0 24 Jul 2019
Mitigating Uncertainty in Document Classification Xuchao Zhang Fanglan Chen Chang-Tien Lu Naren Ramakrishnan 28 42 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 17 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 22 23 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 32 117 0 27 Jun 2019
Model Bridging: Connection between Simulation Model and Neural Network Keiichi Kisamori Keisuke Yamazaki Yuto Komori Hiroshi Tokieda 17 1 0 22 Jun 2019
Disentangling feature and lazy training in deep neural networks Mario Geiger S. Spigler Arthur Jacot Matthieu Wyart 17 17 0 19 Jun 2019
Learning Curves for Deep Neural Networks: A Gaussian Field Theory Perspective Omry Cohen Orit Malka Zohar Ringel AI4CE 29 21 0 12 Jun 2019
The Normalization Method for Alleviating Pathological Sharpness in Wide Neural Networks Ryo Karakida S. Akaho S. Amari 29 40 0 07 Jun 2019
Approximate Inference Turns Deep Networks into Gaussian Processes Mohammad Emtiyaz Khan Alexander Immer Ehsan Abedi M. Korzepa UQCV BDL 47 123 0 05 Jun 2019
Deep ReLU Networks Have Surprisingly Few Activation Patterns Boris Hanin David Rolnick 33 224 0 03 Jun 2019
A Mean Field Theory of Quantized Deep Networks: The Quantization-Depth Trade-Off Yaniv Blumenfeld D. Gilboa Daniel Soudry MQ 21 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 22 53 0 03 Jun 2019
On the Inductive Bias of Neural Tangent Kernels A. Bietti Julien Mairal 28 253 0 29 May 2019
Implicit Rugosity Regularization via Data Augmentation Daniel LeJeune Randall Balestriero Hamid Javadi Richard G. Baraniuk 18 4 0 28 May 2019
Infinitely deep neural networks as diffusion processes Stefano Peluchetti Stefano Favaro ODL 33 31 0 27 May 2019
Scalable Training of Inference Networks for Gaussian-Process Models Jiaxin Shi Mohammad Emtiyaz Khan Jun Zhu BDL 27 18 0 27 May 2019
Interpretable deep Gaussian processes with moments Chi-Ken Lu Scott Cheng-Hsin Yang Xiaoran Hao Patrick Shafto 36 19 0 27 May 2019
Learning spectrograms with convolutional spectral kernels Zheyan Shen Markus Heinonen Samuel Kaski 25 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 26 48 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 33 86 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 30 57 0 09 May 2019
Similarity of Neural Network Representations Revisited Simon Kornblith Mohammad Norouzi Honglak Lee Geoffrey E. Hinton 90 1,365 0 01 May 2019
LS-SVR as a Bayesian RBF network Diego Mesquita Luis A. Freitas Joao P. P. Gomes C. L. C. Mattos 17 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 70 909 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 27 25 0 21 Apr 2019
A Bayesian Perspective on the Deep Image Prior Zezhou Cheng Matheus Gadelha Subhransu Maji Daniel Sheldon BDL UQCV 14 135 0 16 Apr 2019
Nearest-Neighbor Neural Networks for Geostatistics Haoyu Wang Yawen Guan Brian J. Reich BDL 9 16 0 28 Mar 2019
Functional Variational Bayesian Neural Networks Shengyang Sun Guodong Zhang Jiaxin Shi Roger C. Grosse BDL 27 236 0 14 Mar 2019
Implicit Regularization in Over-parameterized Neural Networks M. Kubo Ryotaro Banno Hidetaka Manabe Masataka Minoji 43 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 14 20 0 27 Feb 2019
Function Space Particle Optimization for Bayesian Neural Networks Ziyu Wang Tongzheng Ren Jun Zhu Bo Zhang BDL 28 64 0 26 Feb 2019
A Mean Field Theory of Batch Normalization Greg Yang Jeffrey Pennington Vinay Rao Jascha Narain Sohl-Dickstein S. Schoenholz 27 178 0 21 Feb 2019
On the Impact of the Activation Function on Deep Neural Networks Training Soufiane Hayou Arnaud Doucet Judith Rousseau ODL 31 195 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 57 1,080 0 18 Feb 2019
Bayesian Image Classification with Deep Convolutional Gaussian Processes Vincent Dutordoir Mark van der Wilk A. Artemev J. Hensman UQCV BDL 30 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 16 284 0 13 Feb 2019
Mean Field Limit of the Learning Dynamics of Multilayer Neural Networks Phan-Minh Nguyen AI4CE 24 72 0 07 Feb 2019
The role of a layer in deep neural networks: a Gaussian Process perspective Oded Ben-David Zohar Ringel AI4CE 11 3 0 06 Feb 2019
The Benefits of Over-parameterization at Initialization in Deep ReLU Networks Devansh Arpit Yoshua Bengio 19 22 0 11 Jan 2019
On the effect of the activation function on the distribution of hidden nodes in a deep network Philip M. Long Hanie Sedghi 29 5 0 07 Jan 2019
Scaling description of generalization with number of parameters in deep learning Mario Geiger Arthur Jacot S. Spigler Franck Gabriel Levent Sagun Stéphane dÁscoli Giulio Biroli Clément Hongler Matthieu Wyart 52 195 0 06 Jan 2019
On Lazy Training in Differentiable Programming Lénaïc Chizat Edouard Oyallon Francis R. Bach 58 809 0 19 Dec 2018
Efficient Model-Free Reinforcement Learning Using Gaussian Process Ying Fan Letian Chen Yizhou Wang GP 31 6 0 11 Dec 2018