Efficient and Scalable Bayesian Neural Nets with Rank-1 Factors

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Efficient and Scalable Bayesian Neural Nets with Rank-1 Factors

14 May 2020

Michael W. Dusenberry

Katherine A. Heller

Balaji Lakshminarayanan

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Papers citing "Efficient and Scalable Bayesian Neural Nets with Rank-1 Factors"

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Title
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 360 1,947 0 12 Nov 2020
Amortized Conditional Normalized Maximum Likelihood: Reliable Out of Distribution Uncertainty Estimation Aurick Zhou Sergey Levine BDL OOD UQCV 43 13 0 05 Nov 2020
Bayesian Deep Learning via Subnetwork Inference Erik A. Daxberger Eric T. Nalisnick J. Allingham Javier Antorán José Miguel Hernández-Lobato UQCV BDL 130 86 0 28 Oct 2020
Combining Ensembles and Data Augmentation can Harm your Calibration Yeming Wen Ghassen Jerfel Rafael Muller Michael W. Dusenberry Jasper Snoek Balaji Lakshminarayanan Dustin Tran UQCV 136 64 0 19 Oct 2020
Towards Compact Neural Networks via End-to-End Training: A Bayesian Tensor Approach with Automatic Rank Determination Cole Hawkins Xing-er Liu Zheng Zhang BDL MQ 97 29 0 17 Oct 2020
Ensemble Distillation for Structured Prediction: Calibrated, Accurate, Fast-Choose Three Steven Reich David Mueller Nicholas Andrews BDL OOD UQCV 54 13 0 13 Oct 2020
Training independent subnetworks for robust prediction Marton Havasi Rodolphe Jenatton Stanislav Fort Jeremiah Zhe Liu Jasper Snoek Balaji Lakshminarayanan Andrew M. Dai Dustin Tran UQCV OOD 106 213 0 13 Oct 2020
DVERGE: Diversifying Vulnerabilities for Enhanced Robust Generation of Ensembles Huanrui Yang Jingyang Zhang Hongliang Dong Nathan Inkawhich Andrew B. Gardner Andrew Touchet Wesley Wilkes Heath Berry H. Li AAML 83 109 0 30 Sep 2020
Action and Perception as Divergence Minimization Danijar Hafner Pedro A. Ortega Jimmy Ba Thomas Parr Karl J. Friston N. Heess 91 53 0 03 Sep 2020
Investigating maximum likelihood based training of infinite mixtures for uncertainty quantification Sina Daubener Asja Fischer BDL UQCV 36 2 0 07 Aug 2020
Bayesian Deep Ensembles via the Neural Tangent Kernel Bobby He Balaji Lakshminarayanan Yee Whye Teh BDL UQCV 66 121 0 11 Jul 2020
URSABench: Comprehensive Benchmarking of Approximate Bayesian Inference Methods for Deep Neural Networks Meet P. Vadera Adam D. Cobb B. Jalaeian Benjamin M. Marlin BDL UQCV 81 17 0 08 Jul 2020
Hyperparameter Ensembles for Robustness and Uncertainty Quantification F. Wenzel Jasper Snoek Dustin Tran Rodolphe Jenatton UQCV 101 212 0 24 Jun 2020
Simple and Principled Uncertainty Estimation with Deterministic Deep Learning via Distance Awareness Jeremiah Zhe Liu Zi Lin Shreyas Padhy Dustin Tran Tania Bedrax-Weiss Balaji Lakshminarayanan UQCV BDL 290 452 0 17 Jun 2020
Depth Uncertainty in Neural Networks Javier Antorán J. Allingham José Miguel Hernández-Lobato UQCV OOD BDL 109 103 0 15 Jun 2020
The Dual Information Bottleneck Zoe Piran Ravid Shwartz-Ziv Naftali Tishby 61 15 0 08 Jun 2020
Global inducing point variational posteriors for Bayesian neural networks and deep Gaussian processes Sebastian W. Ober Laurence Aitchison BDL 116 60 0 17 May 2020
Informative Bayesian Neural Network Priors for Weak Signals Tianyu Cui A. Havulinna Pekka Marttinen Samuel Kaski 55 9 0 24 Feb 2020