Spatio-temporal ecological models via physics-informed neural networks for studying chronic wasting disease-Reference-Cited by-同舟云学术

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Spatio-temporal ecological models via physics-informed neural networks for studying chronic wasting disease

Published:2024-08 Issue: Volume:62 Page:100850
ISSN:2211-6753
Container-title:Spatial Statistics
language:en
Short-container-title:Spatial Statistics

Author:

Mandujano Reyes Juan Francisco^ORCID,Ma Ting Fung,McGahan Ian P.,Storm Daniel J.,Walsh Daniel P.,Zhu Jun

Funder

USDA NIFA

NSF

Publisher

Elsevier BV

Reference52 articles.

1. TensorFlow: Large-scale machine learning on heterogeneous systems;Abadi,2015

2. A natural case of chronic wasting disease in a free-ranging moose (Alces alces shirasi);Baeten;J. Wildl. Dis.,2007

3. Partial differential equation modeling for spatio-temporal analysis of chronic wasting disease in southwestern Wisconsin;Berg,2024

4. Spatial and spatio-temporal models with R-INLA;Blangiardo;Spat. Spatio-temp. Epidemiol.,2013

5. Three ways to solve partial differential equations with neural networks—A review;Blechschmidt;GAMM-Mitt.,2021

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