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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
Adversarial Robustness Guarantees for Random Deep Neural Networks Giacomo De Palma B. Kiani S. Lloyd AAML OOD 64 8 0 13 Apr 2020
On the Neural Tangent Kernel of Deep Networks with Orthogonal Initialization Wei Huang Weitao Du R. Xu 85 38 0 13 Apr 2020
Reinforcement Learning via Gaussian Processes with Neural Network Dual Kernels I. Goumiri Benjamin W. Priest M. Schneider GP BDL 37 7 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 121 23 0 02 Apr 2020
On Infinite-Width Hypernetworks Etai Littwin Tomer Galanti Lior Wolf Greg Yang 117 11 0 27 Mar 2020
B-PINNs: Bayesian Physics-Informed Neural Networks for Forward and Inverse PDE Problems with Noisy Data Liu Yang Xuhui Meng George Karniadakis PINN 260 797 0 13 Mar 2020
FedLoc: Federated Learning Framework for Data-Driven Cooperative Localization and Location Data Processing Feng Yin Zhidi Lin Yue Xu Qinglei Kong Deshi Li Sergios Theodoridis Shuguang Cui Cui FedML 156 4 0 08 Mar 2020
Neural Kernels Without Tangents Vaishaal Shankar Alex Fang Wenshuo Guo Sara Fridovich-Keil Ludwig Schmidt Jonathan Ragan-Kelley Benjamin Recht 81 91 0 04 Mar 2020
The large learning rate phase of deep learning: the catapult mechanism Aitor Lewkowycz Yasaman Bahri Ethan Dyer Jascha Narain Sohl-Dickstein Guy Gur-Ari ODL 244 241 0 04 Mar 2020
Double Trouble in Double Descent : Bias and Variance(s) in the Lazy Regime Stéphane dÁscoli Maria Refinetti Giulio Biroli Florent Krzakala 211 153 0 02 Mar 2020
Stable behaviour of infinitely wide deep neural networks Stefano Favaro S. Fortini Stefano Peluchetti BDL 83 28 0 01 Mar 2020
Convolutional Spectral Kernel Learning Jian Li Yong Liu Weiping Wang BDL 48 5 0 28 Feb 2020
Infinitely Wide Graph Convolutional Networks: Semi-supervised Learning via Gaussian Processes Jilin Hu Jianbing Shen B. Yang Ling Shao BDL GNN 109 18 0 26 Feb 2020
Convex Geometry and Duality of Over-parameterized Neural Networks Tolga Ergen Mert Pilanci MLT 138 56 0 25 Feb 2020
Avoiding Kernel Fixed Points: Computing with ELU and GELU Infinite Networks Russell Tsuchida Tim Pearce Christopher van der Heide Fred Roosta M. Gallagher 75 8 0 20 Feb 2020
Robust Pruning at Initialization Soufiane Hayou Jean-François Ton Arnaud Doucet Yee Whye Teh 43 47 0 19 Feb 2020
Why Do Deep Residual Networks Generalize Better than Deep Feedforward Networks? -- A Neural Tangent Kernel Perspective Kaixuan Huang Yuqing Wang Molei Tao T. Zhao MLT 62 98 0 14 Feb 2020
On Layer Normalization in the Transformer Architecture Ruibin Xiong Yunchang Yang Di He Kai Zheng Shuxin Zheng Chen Xing Huishuai Zhang Yanyan Lan Liwei Wang Tie-Yan Liu AI4CE 160 1,006 0 12 Feb 2020
Taylorized Training: Towards Better Approximation of Neural Network Training at Finite Width Yu Bai Ben Krause Huan Wang Caiming Xiong R. Socher 87 22 0 10 Feb 2020
Quasi-Equivalence of Width and Depth of Neural Networks Fenglei Fan Rongjie Lai Ge Wang 111 11 0 06 Feb 2020
Function approximation by neural nets in the mean-field regime: Entropic regularization and controlled McKean-Vlasov dynamics Belinda Tzen Maxim Raginsky 85 17 0 05 Feb 2020
Gating creates slow modes and controls phase-space complexity in GRUs and LSTMs T. Can K. Krishnamurthy D. Schwab AI4CE 124 18 0 31 Jan 2020
On Random Kernels of Residual Architectures Etai Littwin Tomer Galanti Lior Wolf 68 4 0 28 Jan 2020
On the infinite width limit of neural networks with a standard parameterization Jascha Narain Sohl-Dickstein Roman Novak S. Schoenholz Jaehoon Lee 94 47 0 21 Jan 2020
Disentangling Trainability and Generalization in Deep Neural Networks Lechao Xiao Jeffrey Pennington S. Schoenholz 90 34 0 30 Dec 2019
Discriminative Clustering with Representation Learning with any Ratio of Labeled to Unlabeled Data Corinne Jones Vincent Roulet Zaïd Harchaoui 121 1 0 30 Dec 2019
Mean field theory for deep dropout networks: digging up gradient backpropagation deeply Wei Huang R. Xu Weitao Du Yutian Zeng Yunce Zhao 68 6 0 19 Dec 2019
Analytic expressions for the output evolution of a deep neural network Anastasia Borovykh 43 0 0 18 Dec 2019
On the Bias-Variance Tradeoff: Textbooks Need an Update Brady Neal 43 18 0 17 Dec 2019
On the relationship between multitask neural networks and multitask Gaussian Processes Karthikeyan K S. Bharti Piyush Rai BDL 18 0 0 12 Dec 2019
Location Trace Privacy Under Conditional Priors Casey Meehan Kamalika Chaudhuri 63 8 0 09 Dec 2019
Neural Tangents: Fast and Easy Infinite Neural Networks in Python Roman Novak Lechao Xiao Jiri Hron Jaehoon Lee Alexander A. Alemi Jascha Narain Sohl-Dickstein S. Schoenholz 108 231 0 05 Dec 2019
Implicit Priors for Knowledge Sharing in Bayesian Neural Networks Jack K. Fitzsimons Sebastian M. Schmon Stephen J. Roberts BDL FedML 32 0 0 02 Dec 2019
On the Heavy-Tailed Theory of Stochastic Gradient Descent for Deep Neural Networks Umut Simsekli Mert Gurbuzbalaban T. H. Nguyen G. Richard Levent Sagun 117 59 0 29 Nov 2019
Richer priors for infinitely wide multi-layer perceptrons Russell Tsuchida Fred Roosta M. Gallagher 62 11 0 29 Nov 2019
Convex Formulation of Overparameterized Deep Neural Networks Cong Fang Yihong Gu Weizhong Zhang Tong Zhang 92 28 0 18 Nov 2019
Enhanced Convolutional Neural Tangent Kernels Zhiyuan Li Ruosong Wang Dingli Yu S. Du Wei Hu Ruslan Salakhutdinov Sanjeev Arora 110 133 0 03 Nov 2019
Tensor Programs I: Wide Feedforward or Recurrent Neural Networks of Any Architecture are Gaussian Processes Greg Yang 217 202 0 28 Oct 2019
Explicitly Bayesian Regularizations in Deep Learning Xinjie Lan Kenneth Barner UQCV BDL AI4CE 112 1 0 22 Oct 2019
Aleatoric and Epistemic Uncertainty in Machine Learning: An Introduction to Concepts and Methods Eyke Hüllermeier Willem Waegeman PER UD 274 1,445 0 21 Oct 2019
Why bigger is not always better: on finite and infinite neural networks Laurence Aitchison 251 54 0 17 Oct 2019
Pathological spectra of the Fisher information metric and its variants in deep neural networks Ryo Karakida S. Akaho S. Amari 84 28 0 14 Oct 2019
Large Deviation Analysis of Function Sensitivity in Random Deep Neural Networks Bo Li D. Saad 74 12 0 13 Oct 2019
On the expected behaviour of noise regularised deep neural networks as Gaussian processes Arnu Pretorius Herman Kamper Steve Kroon 66 9 0 12 Oct 2019
The Expressivity and Training of Deep Neural Networks: toward the Edge of Chaos? Gege Zhang Gang-cheng Li Ningwei Shen Weidong Zhang 85 6 0 11 Oct 2019
Harnessing the Power of Infinitely Wide Deep Nets on Small-data Tasks Sanjeev Arora S. Du Zhiyuan Li Ruslan Salakhutdinov Ruosong Wang Dingli Yu AAML 89 162 0 03 Oct 2019
Beyond Linearization: On Quadratic and Higher-Order Approximation of Wide Neural Networks Yu Bai Jason D. Lee 85 116 0 03 Oct 2019
Truth or Backpropaganda? An Empirical Investigation of Deep Learning Theory Micah Goldblum Jonas Geiping Avi Schwarzschild Michael Moeller Tom Goldstein 135 34 0 01 Oct 2019
The asymptotic spectrum of the Hessian of DNN throughout training Arthur Jacot Franck Gabriel Clément Hongler 145 35 0 01 Oct 2019
Non-Gaussian processes and neural networks at finite widths Sho Yaida 117 88 0 30 Sep 2019