Spatio-Temporal PRRS Epidemic Forecasting via Factorized Deep Generative Modeling-Reference-Cited by-同舟云学术

Spatio-Temporal PRRS Epidemic Forecasting via Factorized Deep Generative Modeling

Published:2022-05-23 Issue: Volume: Page:
ISSN:
Container-title:ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
language:
Short-container-title:

Author:

Shamsabardeh Mohammadsadegh¹,Azari Bahar²,Martinez-Lopez Beatriz¹

Affiliation:

1. University of California,Center for Animal Disease Modeling and Surveillance,Davis,CA,USA

2. Northeastern University,Boston,MA,USA

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9745891/9746004/09747564.pdf?arnumber=9747564

Reference21 articles.

1. Switching linear dynamics for variational bayes filtering;becker-ehmck,2019

2. A novel way to predict PRRS outbreaks in the swine industry using multiple spatio-temporal features and machine learning approaches

3. On random graphs i;erdos;Publicationes Mathematicae (Debrecen),1959

4. Modeling the spread of porcine reproductive and respiratory syndrome virus (prrsv) in a swine population: transmission dynamics, immunity information, and optimal control strategies;phoongurn;Advances in Difference Equations,2019

5. Infectiousness of pigs infected by the Porcine Reproductive and Respiratory Syndrome virus (PRRSV) is time-dependent

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Multi-Resolution Sequence Aggregation and Model-Agnostic Framework for Time-Series Forecasting;ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP);2023-06-04