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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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Reducing the Amortization Gap in Variational Autoencoders: A Bayesian Random Function Approach Minyoung Kim Vladimir Pavlovic BDL 107 6 0 05 Feb 2021
Variational Bayes survival analysis for unemployment modelling P. Boškoski M. Perne M. Ramesa Biljana Mileva-Boshkoska CML 67 10 0 03 Feb 2021
A Statistician Teaches Deep Learning G. Babu David L. Banks Hyunsoo Cho David Han Hailin Sang Shouyi Wang 82 2 0 29 Jan 2021
Faster Kernel Interpolation for Gaussian Processes Mohit Yadav Daniel Sheldon Cameron Musco BDL 47 10 0 28 Jan 2021
A Similarity Measure of Gaussian Process Predictive Distributions Lucia Asencio-Martín Eduardo C. Garrido-Merchán 43 1 0 20 Jan 2021
Implicit Bias of Linear RNNs M Motavali Emami Mojtaba Sahraee-Ardakan Parthe Pandit S. Rangan A. Fletcher 59 11 0 19 Jan 2021
Correlated Weights in Infinite Limits of Deep Convolutional Neural Networks Adrià Garriga-Alonso Mark van der Wilk 63 4 0 11 Jan 2021
Scaling Up Bayesian Uncertainty Quantification for Inverse Problems using Deep Neural Networks Shiwei Lan Shuyi Li Babak Shahbaba UQCV BDL 106 16 0 11 Jan 2021
Infinitely Wide Tensor Networks as Gaussian Process Erdong Guo D. Draper 101 2 0 07 Jan 2021
The Bayesian Method of Tensor Networks Erdong Guo D. Draper 88 3 0 01 Jan 2021
Perspective: A Phase Diagram for Deep Learning unifying Jamming, Feature Learning and Lazy Training Mario Geiger Leonardo Petrini Matthieu Wyart DRL 79 11 0 30 Dec 2020
Mathematical Models of Overparameterized Neural Networks Cong Fang Hanze Dong Tong Zhang 181 23 0 27 Dec 2020
Tight Bounds on the Smallest Eigenvalue of the Neural Tangent Kernel for Deep ReLU Networks Quynh N. Nguyen Marco Mondelli Guido Montúfar 140 83 0 21 Dec 2020
Defence against adversarial attacks using classical and quantum-enhanced Boltzmann machines Aidan Kehoe P. Wittek Yanbo Xue Alejandro Pozas-Kerstjens AAML 84 7 0 21 Dec 2020
Recent advances in deep learning theory Fengxiang He Dacheng Tao AI4CE 138 51 0 20 Dec 2020
Multi-fidelity Bayesian Neural Networks: Algorithms and Applications Xuhui Meng H. Babaee George Karniadakis 74 132 0 19 Dec 2020
Guiding Neural Network Initialization via Marginal Likelihood Maximization Anthony S. Tai Chunfeng Huang 32 0 0 17 Dec 2020
Enhanced Recurrent Neural Tangent Kernels for Non-Time-Series Data Sina Alemohammad Randall Balestriero Zichao Wang Richard Baraniuk AI4TS 46 1 0 09 Dec 2020
Analyzing Finite Neural Networks: Can We Trust Neural Tangent Kernel Theory? Mariia Seleznova Gitta Kutyniok AAML 88 30 0 08 Dec 2020
Generalization bounds for deep learning Guillermo Valle Pérez A. Louis BDL 84 45 0 07 Dec 2020
Statistical Mechanics of Deep Linear Neural Networks: The Back-Propagating Kernel Renormalization Qianyi Li H. Sompolinsky 195 73 0 07 Dec 2020
Neural Network Gaussian Process Considering Input Uncertainty for Composite Structures Assembly Cheolhei Lee Jianguo Wu Wei Cao Xiaowei Yue 57 19 0 21 Nov 2020
On the Dynamics of Training Attention Models Haoye Lu Yongyi Mao A. Nayak 47 8 0 19 Nov 2020
A Review of Uncertainty Quantification in Deep Learning: Techniques, Applications and Challenges Moloud Abdar Farhad Pourpanah Sadiq Hussain Dana Rezazadegan Li Liu ... Xiaochun Cao Abbas Khosravi U. Acharya V. Makarenkov S. Nahavandi BDL UQCV 385 1,952 0 12 Nov 2020
Towards NNGP-guided Neural Architecture Search Daniel S. Park Jaehoon Lee Daiyi Peng Yuan Cao Jascha Narain Sohl-Dickstein BDL 71 34 0 11 Nov 2020
Kernel Dependence Network Chieh-Tsai Wu A. Masoomi Arthur Gretton Jennifer Dy 46 0 0 04 Nov 2020
Which Minimizer Does My Neural Network Converge To? Manuel Nonnenmacher David Reeb Ingo Steinwart ODL 51 4 0 04 Nov 2020
Dataset Meta-Learning from Kernel Ridge-Regression Timothy Nguyen Zhourung Chen Jaehoon Lee DD 198 247 0 30 Oct 2020
Do Wide and Deep Networks Learn the Same Things? Uncovering How Neural Network Representations Vary with Width and Depth Thao Nguyen M. Raghu Simon Kornblith OOD 121 284 0 29 Oct 2020
A Bayesian Perspective on Training Speed and Model Selection Clare Lyle Lisa Schut Binxin Ru Y. Gal Mark van der Wilk 102 24 0 27 Oct 2020
Are wider nets better given the same number of parameters? A. Golubeva Behnam Neyshabur Guy Gur-Ari 112 44 0 27 Oct 2020
A Probabilistic Representation of Deep Learning for Improving The Information Theoretic Interpretability Xinjie Lan Kenneth Barner FAtt 45 2 0 27 Oct 2020
Wearing a MASK: Compressed Representations of Variable-Length Sequences Using Recurrent Neural Tangent Kernels Sina Alemohammad Hossein Babaei Randall Balestriero Matt Y. Cheung Ahmed Imtiaz Humayun ... Naiming Liu Lorenzo Luzi Jasper Tan Zichao Wang Richard G. Baraniuk 36 5 0 27 Oct 2020
Stable ResNet Soufiane Hayou Eugenio Clerico Bo He George Deligiannidis Arnaud Doucet Judith Rousseau ODL SSeg 105 53 0 24 Oct 2020
Label-Aware Neural Tangent Kernel: Toward Better Generalization and Local Elasticity Shuxiao Chen Hangfeng He Weijie J. Su 62 24 0 22 Oct 2020
Stationary Activations for Uncertainty Calibration in Deep Learning Lassi Meronen Christabella Irwanto Arno Solin UQCV BDL 56 19 0 19 Oct 2020
The Ridgelet Prior: A Covariance Function Approach to Prior Specification for Bayesian Neural Networks Takuo Matsubara Chris J. Oates F. Briol BDL UQCV 64 19 0 16 Oct 2020
Exploring the Uncertainty Properties of Neural Networks' Implicit Priors in the Infinite-Width Limit Ben Adlam Jaehoon Lee Lechao Xiao Jeffrey Pennington Jasper Snoek UQCV BDL 76 16 0 14 Oct 2020
Machine Learning Force Fields Oliver T. Unke Stefan Chmiela H. E. Sauceda M. Gastegger I. Poltavsky Kristof T. Schütt A. Tkatchenko K. Müller AI4CE 154 940 0 14 Oct 2020
Improving Local Identifiability in Probabilistic Box Embeddings S. Dasgupta Michael Boratko Dongxu Zhang Luke Vilnis Xiang Lorraine Li Andrew McCallum 78 54 0 09 Oct 2020
Ensembling geophysical models with Bayesian Neural Networks Ushnish Sengupta Matt Amos J. S. Hosking C. Rasmussen M. Juniper P. Young UQCV BDL 24 17 0 07 Oct 2020
An Infinite-Feature Extension for Bayesian ReLU Nets That Fixes Their Asymptotic Overconfidence Agustinus Kristiadi Matthias Hein Philipp Hennig BDL 79 9 0 06 Oct 2020
Deep kernel processes Laurence Aitchison Adam X. Yang Sebastian W. Ober BDL 102 42 0 04 Oct 2020
Uncertainty-Aware Multi-Modal Ensembling for Severity Prediction of Alzheimer's Dementia U. Sarawgi W. Zulfikar Rishab Khincha Pattie Maes UQCV 44 2 0 03 Oct 2020
Deep Equals Shallow for ReLU Networks in Kernel Regimes A. Bietti Francis R. Bach 129 90 0 30 Sep 2020
Normalization Techniques in Training DNNs: Methodology, Analysis and Application Lei Huang Jie Qin Yi Zhou Fan Zhu Li Liu Ling Shao AI4CE 180 278 0 27 Sep 2020
Why have a Unified Predictive Uncertainty? Disentangling it using Deep Split Ensembles U. Sarawgi W. Zulfikar Rishab Khincha Pattie Maes PER UQCV BDL UD 61 7 0 25 Sep 2020
Tensor Programs III: Neural Matrix Laws Greg Yang 100 48 0 22 Sep 2020
Kernel-Based Smoothness Analysis of Residual Networks Tom Tirer Joan Bruna Raja Giryes 82 20 0 21 Sep 2020
InClass Nets: Independent Classifier Networks for Nonparametric Estimation of Conditional Independence Mixture Models and Unsupervised Classification Konstantin T. Matchev Prasanth Shyamsundar CML 75 0 0 31 Aug 2020