When in Doubt: Neural Non-Parametric Uncertainty Quantification for
Epidemic Forecasting

When in Doubt: Neural Non-Parametric Uncertainty Quantification for Epidemic Forecasting

7 June 2021

Harshavardhan Kamarthi

Lingkai Kong

Alexander Rodríguez

Papers citing "When in Doubt: Neural Non-Parametric Uncertainty Quantification for Epidemic Forecasting"

6 / 6 papers shown

Title
When Rigidity Hurts: Soft Consistency Regularization for Probabilistic Hierarchical Time Series Forecasting Harshavardhan Kamarthi Lingkai Kong Alexander Rodríguez Chao Zhang B. Prakash AI4TS 30 5 0 17 Oct 2023
End-to-End Stochastic Optimization with Energy-Based Model Lingkai Kong Jiaming Cui Yuchen Zhuang Rui Feng B. Prakash Chao Zhang 13 16 0 25 Nov 2022
Data-Centric Epidemic Forecasting: A Survey Alexander Rodríguez Harshavardhan Kamarthi Pulak Agarwal Javen Ho Mira Patel Suchet Sapre B. Prakash OOD 26 18 0 19 Jul 2022
SDE-Net: Equipping Deep Neural Networks with Uncertainty Estimates Lingkai Kong Jimeng Sun Chao Zhang UQCV 44 103 0 24 Aug 2020
Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles Balaji Lakshminarayanan Alexander Pritzel Charles Blundell UQCV BDL 270 5,660 0 05 Dec 2016
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning Y. Gal Zoubin Ghahramani UQCV BDL 285 9,136 0 06 Jun 2015