Faithful Heteroscedastic Regression with Neural Networks

Faithful Heteroscedastic Regression with Neural Networks

18 December 2022

Megan D. Schertzer

Neville E. Sanjana

David A. Knowles

Papers citing "Faithful Heteroscedastic Regression with Neural Networks"

15 / 15 papers shown

Title
On the Pitfalls of Heteroscedastic Uncertainty Estimation with Probabilistic Neural Networks Maximilian Seitzer Arash Tavakoli Dimitrije Antic Georg Martius BDL UQCV 55 84 0 17 Mar 2022
Variational Variance: Simple, Reliable, Calibrated Heteroscedastic Noise Variance Parameterization Andrew Stirn David A. Knowles DRL 40 10 0 08 Jun 2020
MOPO: Model-based Offline Policy Optimization Tianhe Yu G. Thomas Lantao Yu Stefano Ermon James Zou Sergey Levine Chelsea Finn Tengyu Ma OffRL 74 759 0 27 May 2020
Decision-Making with Auto-Encoding Variational Bayes Romain Lopez Pierre Boyeau Nir Yosef Michael I. Jordan Jeffrey Regier BDL 267 10,591 0 17 Feb 2020
Reliable training and estimation of variance networks N. Detlefsen Martin Jørgensen Søren Hauberg UQCV 49 86 0 04 Jun 2019
Accurate Uncertainties for Deep Learning Using Calibrated Regression Volodymyr Kuleshov Nathan Fenner Stefano Ermon BDL UQCV 160 626 0 01 Jul 2018
Deep Reinforcement Learning in a Handful of Trials using Probabilistic Dynamics Models Kurtland Chua Roberto Calandra R. McAllister Sergey Levine BDL 188 1,263 0 30 May 2018
A Unified Approach to Interpreting Model Predictions Scott M. Lundberg Su-In Lee FAtt 718 21,613 0 22 May 2017
What Uncertainties Do We Need in Bayesian Deep Learning for Computer Vision? Alex Kendall Y. Gal BDL OOD UD UQCV PER 317 4,667 0 15 Mar 2017
Deep Bayesian Active Learning with Image Data Y. Gal Riashat Islam Zoubin Ghahramani BDL UQCV 64 1,717 0 08 Mar 2017
Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles Balaji Lakshminarayanan Alexander Pritzel Charles Blundell UQCV BDL 564 5,748 0 05 Dec 2016
Deep Exploration via Bootstrapped DQN Ian Osband Charles Blundell Alexander Pritzel Benjamin Van Roy 80 1,302 0 15 Feb 2016
Deep Kernel Learning A. Wilson Zhiting Hu Ruslan Salakhutdinov Eric Xing BDL 206 882 0 06 Nov 2015
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning Y. Gal Zoubin Ghahramani UQCV BDL 550 9,233 0 06 Jun 2015
Adam: A Method for Stochastic Optimization Diederik P. Kingma Jimmy Ba ODL 1.2K 149,474 0 22 Dec 2014

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