Machine learning for data-centric epidemic forecasting
The COVID-19 pandemic emphasized the importance of epidemic forecasting for decision
makers in multiple domains, ranging from public health to the economy. Forecasting …
makers in multiple domains, ranging from public health to the economy. Forecasting …
Einns: epidemiologically-informed neural networks
We introduce EINNs, a framework crafted for epidemic forecasting that builds upon the
theoretical grounds provided by mechanistic models as well as the data-driven expressibility …
theoretical grounds provided by mechanistic models as well as the data-driven expressibility …
A mobility forecasting framework with vertical federated learning
FZ Errounda, Y Liu - 2022 IEEE 46th Annual Computers …, 2022 - ieeexplore.ieee.org
With the prevalence of mobile devices and location-based services, forecasting human
mobility has become a critical topic in ubiquitous computing. Existing forecasting …
mobility has become a critical topic in ubiquitous computing. Existing forecasting …
MTSNet: Deep probabilistic cross-multivariate time series modeling with external factors for COVID-19
Y Yang, L Cao - 2023 International Joint Conference on Neural …, 2023 - ieeexplore.ieee.org
Complex intelligent systems such as for tackling the COVID-19 pandemic involve multiple
multivariate time series (MTSs), where both target variables (such as COVID-19 infected …
multivariate time series (MTSs), where both target variables (such as COVID-19 infected …
H2ABM: Heterogeneous Agent-based Model on Hypergraphs to Capture Group Interactions
Heterogeneous agent-based models (HABMs) can simulate the dynamics of multiple types
of entities and their interactions on contact networks. In recent years, they have gathered …
of entities and their interactions on contact networks. In recent years, they have gathered …
Explainable Prediction of the Severity of COVID-19 Outbreak for US Counties
Ever since the COVID-19 outbreak, various works have focused on using multitude of
different static and dynamic features to aid the prediction of disease forecasting models …
different static and dynamic features to aid the prediction of disease forecasting models …
Deep Probabilistic Modeling for Coupled Multivariate Time Series
Y Yang - 2023 - opus.lib.uts.edu.au
Some complex intelligent systems such as for tackling the COVID-19 pandemic involve
coupled Multivariate Time Series (MTSs), where both target variables (such as COVID-19 …
coupled Multivariate Time Series (MTSs), where both target variables (such as COVID-19 …
Adaptive Differential Privacy for Decentralized Mobility Data Sharing and Forecasting
FZ Errounda - 2023 - spectrum.library.concordia.ca
Mobility data is the cornerstone of crucial applications, including traffic monitoring,
crowdsourcing, and social networks. However, research shows that publishing accurate …
crowdsourcing, and social networks. However, research shows that publishing accurate …