TIC-TAC: A Framework for Improved Covariance Estimation in Deep
Heteroscedastic Regression

TIC-TAC: A Framework for Improved Covariance Estimation in Deep Heteroscedastic Regression

29 October 2023

Mathieu Salzmann

Alexandre Alahi

Papers citing "TIC-TAC: A Framework for Improved Covariance Estimation in Deep Heteroscedastic Regression"

4 / 4 papers shown

Title
Scalable Dynamic Mixture Model with Full Covariance for Probabilistic Traffic Forecasting Seongjin Choi Nicolas Saunier Vincent Zhihao Zheng M. Trépanier Lijun Sun 4 1 0 10 Dec 2022
Bayesian Model Selection, the Marginal Likelihood, and Generalization Sanae Lotfi Pavel Izmailov Gregory W. Benton Micah Goldblum A. Wilson UQCV BDL 45 55 0 23 Feb 2022
Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles Balaji Lakshminarayanan Alexander Pritzel Charles Blundell UQCV BDL 268 5,635 0 05 Dec 2016
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning Y. Gal Zoubin Ghahramani UQCV BDL 247 9,042 0 06 Jun 2015