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Bayesian Deep Ensembles via the Neural Tangent Kernel

11 July 2020

Bobby He

Balaji Lakshminarayanan

Papers citing "Bayesian Deep Ensembles via the Neural Tangent Kernel"

35 / 85 papers shown

Title
Incorporating Prior Knowledge into Neural Networks through an Implicit Composite Kernel Ziyang Jiang Tongshu Zheng Yiling Liu David Carlson 73 4 0 15 May 2022
Deep Ensemble as a Gaussian Process Approximate Posterior Zhijie Deng Feng Zhou Jianfei Chen Guoqiang Wu Jun Zhu UQCV 46 5 0 30 Apr 2022
Contrasting random and learned features in deep Bayesian linear regression Jacob A. Zavatone-Veth William L. Tong Cengiz Pehlevan BDL MLT 137 28 0 01 Mar 2022
Theoretical Error Analysis of Entropy Approximation for Gaussian Mixture Takashi Furuya Hiroyuki Kusumoto K. Taniguchi Naoya Kanno Kazuma Suetake 88 1 0 26 Feb 2022
Embedded Ensembles: Infinite Width Limit and Operating Regimes Maksim Velikanov Roma Kail Ivan Anokhin Roman Vashurin Maxim Panov Alexey Zaytsev Dmitry Yarotsky 49 1 0 24 Feb 2022
Wide Mean-Field Bayesian Neural Networks Ignore the Data Beau Coker W. Bruinsma David R. Burt Weiwei Pan Finale Doshi-Velez UQCV BDL 89 24 0 23 Feb 2022
UncertaINR: Uncertainty Quantification of End-to-End Implicit Neural Representations for Computed Tomography Francisca Vasconcelos Bobby He Nalini Singh Yee Whye Teh BDL OOD UQCV 76 13 0 22 Feb 2022
Deep Ensembles Work, But Are They Necessary? Taiga Abe E. Kelly Buchanan Geoff Pleiss R. Zemel John P. Cunningham OOD UQCV 147 65 0 14 Feb 2022
An Overview of Uncertainty Quantification Methods for Infinite Neural Networks Florian Juengermann Maxime Laasri Marius Merkle BDL 36 0 0 13 Jan 2022
Empirical analysis of representation learning and exploration in neural kernel bandits Michal Lisicki Arash Afkanpour Graham W. Taylor 55 0 0 05 Nov 2021
Quantifying Epistemic Uncertainty in Deep Learning Ziyi Huang Henry Lam Haofeng Zhang UQCV BDL UD PER 134 14 0 23 Oct 2021
Conditional Variational Autoencoder for Learned Image Reconstruction Chen Zhang Riccardo Barbano Bangti Jin DRL 51 20 0 22 Oct 2021
The Neural Testbed: Evaluating Joint Predictions Ian Osband Zheng Wen S. Asghari Vikranth Dwaracherla Botao Hao M. Ibrahimi Dieterich Lawson Xiuyuan Lu Brendan O'Donoghue Benjamin Van Roy UQCV 94 22 0 09 Oct 2021
Prior and Posterior Networks: A Survey on Evidential Deep Learning Methods For Uncertainty Estimation Dennis Ulmer Christian Hardmeier J. Frellsen BDL UQCV UD EDL PER 150 55 0 06 Oct 2021
Marginally calibrated response distributions for end-to-end learning in autonomous driving Clara Hoffmann Nadja Klein 89 2 0 03 Oct 2021
Trust Your Robots! Predictive Uncertainty Estimation of Neural Networks with Sparse Gaussian Processes Jongseo Lee Jianxiang Feng Matthias Humt M. Müller Rudolph Triebel UQCV 92 21 0 20 Sep 2021
Reliable Neural Networks for Regression Uncertainty Estimation Tony Tohme Kevin Vanslette K. Youcef-Toumi UQCV BDL 85 15 0 16 Sep 2021
A framework for benchmarking uncertainty in deep regression F. Schmähling Jörg Martin Clemens Elster UQCV 64 8 0 10 Sep 2021
Epistemic Neural Networks Ian Osband Zheng Wen M. Asghari Vikranth Dwaracherla M. Ibrahimi Xiyuan Lu Benjamin Van Roy UQCV BDL 136 109 0 19 Jul 2021
Repulsive Deep Ensembles are Bayesian Francesco DÁngelo Vincent Fortuin UQCV BDL 129 101 0 22 Jun 2021
A self consistent theory of Gaussian Processes captures feature learning effects in finite CNNs Gadi Naveh Zohar Ringel SSL MLT 91 33 0 08 Jun 2021
Greedy Bayesian Posterior Approximation with Deep Ensembles A. Tiulpin Matthew B. Blaschko UQCV FedML 91 4 0 29 May 2021
Deep Ensembles from a Bayesian Perspective L. Hoffmann Clemens Elster UD BDL UQCV 74 38 0 27 May 2021
Priors in Bayesian Deep Learning: A Review Vincent Fortuin UQCV BDL 137 134 0 14 May 2021
Uncertainty-aware Remaining Useful Life predictor Luca Biggio Alexander Wieland M. A. Chao I. Kastanis Olga Fink AI4CE 32 7 0 08 Apr 2021
MixMo: Mixing Multiple Inputs for Multiple Outputs via Deep Subnetworks Alexandre Ramé Rémy Sun Matthieu Cord UQCV 108 61 0 10 Mar 2021
Deep Deterministic Uncertainty: A Simple Baseline Jishnu Mukhoti Andreas Kirsch Joost R. van Amersfoort Philip Torr Y. Gal UD UQCV PER BDL 129 156 0 23 Feb 2021
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 373 1,951 0 12 Nov 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
Stable ResNet Soufiane Hayou Eugenio Clerico Bo He George Deligiannidis Arnaud Doucet Judith Rousseau ODL SSeg 103 53 0 24 Oct 2020
BayesAdapter: Being Bayesian, Inexpensively and Reliably, via Bayesian Fine-tuning Zhijie Deng Jun Zhu BDL 48 9 0 05 Oct 2020
On Power Laws in Deep Ensembles E. Lobacheva Nadezhda Chirkova M. Kodryan Dmitry Vetrov UQCV 75 40 0 16 Jul 2020
Neural Ensemble Search for Uncertainty Estimation and Dataset Shift Sheheryar Zaidi Arber Zela T. Elsken Chris Holmes Frank Hutter Yee Whye Teh OOD UQCV 130 75 0 15 Jun 2020
PIVEN: A Deep Neural Network for Prediction Intervals with Specific Value Prediction Eli Simhayev Gilad Katz Lior Rokach OOD 51 12 0 09 Jun 2020
Universal Statistics of Fisher Information in Deep Neural Networks: Mean Field Approach Ryo Karakida S. Akaho S. Amari FedML 201 146 0 04 Jun 2018