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

7 June 2021

Harshavardhan Kamarthi

Lingkai Kong

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

21 / 21 papers shown

Title
Steering a Historical Disease Forecasting Model Under a Pandemic: Case of Flu and COVID-19 Alexander Rodríguez Nikhil Muralidhar B. Adhikari Anika Tabassum Naren Ramakrishnan B. Prakash LLMSV 24 27 0 23 Sep 2020
SDE-Net: Equipping Deep Neural Networks with Uncertainty Estimates Lingkai Kong Jimeng Sun Chao Zhang UQCV 83 106 0 24 Aug 2020
When and How to Lift the Lockdown? Global COVID-19 Scenario Analysis and Policy Assessment using Compartmental Gaussian Processes Zhaozhi Qian Ahmed Alaa M. Schaar 46 33 0 13 May 2020
Decision-Making with Auto-Encoding Variational Bayes Romain Lopez Pierre Boyeau Nir Yosef Michael I. Jordan Jeffrey Regier BDL 298 10,591 0 17 Feb 2020
Recurrent Attentive Neural Process for Sequential Data Shenghao Qin Jiacheng Zhu Jimmy Qin Wenshuo Wang Ding Zhao BDL AI4TS 66 38 0 17 Oct 2019
The Functional Neural Process Christos Louizos Xiahan Shi Klamer Schutte Max Welling BDL 56 77 0 19 Jun 2019
Distribution Calibration for Regression Hao Song Tom Diethe Meelis Kull Peter A. Flach UQCV 136 110 0 15 May 2019
Cyclical Stochastic Gradient MCMC for Bayesian Deep Learning Ruqi Zhang Chunyuan Li Jianyi Zhang Changyou Chen A. Wilson BDL 72 275 0 11 Feb 2019
Attentive Neural Processes Hyunjik Kim A. Mnih Jonathan Richard Schwarz M. Garnelo S. M. Ali Eslami Dan Rosenbaum Oriol Vinyals Yee Whye Teh 88 440 0 17 Jan 2019
Neural Processes M. Garnelo Jonathan Richard Schwarz Dan Rosenbaum Fabio Viola Danilo Jimenez Rezende S. M. Ali Eslami Yee Whye Teh BDL UQCV GP 81 514 0 04 Jul 2018
Accurate Uncertainties for Deep Learning Using Calibrated Regression Volodymyr Kuleshov Nathan Fenner Stefano Ermon BDL UQCV 166 631 0 01 Jul 2018
On Calibration of Modern Neural Networks Chuan Guo Geoff Pleiss Yu Sun Kilian Q. Weinberger UQCV 237 5,812 0 14 Jun 2017
Attention Is All You Need Ashish Vaswani Noam M. Shazeer Niki Parmar Jakob Uszkoreit Llion Jones Aidan Gomez Lukasz Kaiser Illia Polosukhin 3DV 622 130,942 0 12 Jun 2017
Bayesian Recurrent Neural Networks Meire Fortunato Charles Blundell Oriol Vinyals BDL 53 184 0 10 Apr 2017
Multiplicative Normalizing Flows for Variational Bayesian Neural Networks Christos Louizos Max Welling BDL 141 459 0 06 Mar 2017
Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles Balaji Lakshminarayanan Alexander Pritzel Charles Blundell UQCV BDL 628 5,798 0 05 Dec 2016
Categorical Reparameterization with Gumbel-Softmax Eric Jang S. Gu Ben Poole BDL 273 5,360 0 03 Nov 2016
Preconditioned Stochastic Gradient Langevin Dynamics for Deep Neural Networks Chunyuan Li Changyou Chen David Carlson Lawrence Carin ODL BDL 79 325 0 23 Dec 2015
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning Y. Gal Zoubin Ghahramani UQCV BDL 614 9,290 0 06 Jun 2015
Neural Machine Translation by Jointly Learning to Align and Translate Dzmitry Bahdanau Kyunghyun Cho Yoshua Bengio AIMat 499 27,263 0 01 Sep 2014
Learning Phrase Representations using RNN Encoder-Decoder for Statistical Machine Translation Kyunghyun Cho B. V. Merrienboer Çağlar Gülçehre Dzmitry Bahdanau Fethi Bougares Holger Schwenk Yoshua Bengio AIMat 808 23,310 0 03 Jun 2014