Ensemble forecasting of the Zika space-time spread with topological data analysis

DOI10.1002/env.2629zbMATH Open1545.62941MaRDI QIDQ6626178

Yulia R. Gel, Vyacheslav Lyubchich, Marwah Soliman

Publication date: 28 October 2024

Published in: Environmetrics (Search for Journal in Brave)

zbMATH Keywords

neural networkepidemicsmachine learningBayesian model averagingZika virus

Mathematics Subject Classification ID

Applications of statistics to environmental and related topics (62P12)

Cites Work

• Unnamed Item
• Greedy function approximation: A gradient boosting machine.
• A hybrid particle swarm optimization-back-propagation algorithm for feedforward neural network training
• Bayesian model averaging: A tutorial. (with comments and a rejoinder).
• Computing persistent homology
• Topological data analysis of financial time series: landscapes of crashes
• Topology and data
• Random forests
• Stochastic gradient boosting.
• Spatio–temporal modeling for disease mapping using CAR and B‐spline smoothing
• Bayesian Model Averaging: A Systematic Review and Conceptual Classification
• The Elements of Statistical Learning
• A large-scale spatio-temporal binomial regression model for estimating seroprevalence trends
• Deep echo state networks with uncertainty quantification for spatio-temporal forecasting
• Unsupervised space-time clustering using persistent homology
• Harnessing the power of topological data analysis to detect change points

This page was built for publication: Ensemble forecasting of the Zika space-time spread with topological data analysis