A review of graph neural networks in epidemic modeling
Since the onset of the COVID-19 pandemic, there has been a growing interest in studying
epidemiological models. Traditional mechanistic models mathematically describe the …
epidemiological models. Traditional mechanistic models mathematically describe the …
A survey on data-driven covid-19 and future pandemic management
The COVID-19 pandemic has resulted in more than 440 million confirmed cases globally
and almost 6 million reported deaths as of March 2022. Consequently, the world …
and almost 6 million reported deaths as of March 2022. Consequently, the world …
Epidemic versus economic performances of the COVID-19 lockdown: A big data driven analysis
Lockdown measures have been a “panacea” for pandemic control but also a violent “poison”
for economies. Lockdown policies strongly restrict human mobility but mobility reduce does …
for economies. Lockdown policies strongly restrict human mobility but mobility reduce does …
Cluster-aware grid layout
Grid visualizations are widely used in many applications to visually explain a set of data and
their proximity relationships. However, existing layout methods face difficulties when dealing …
their proximity relationships. However, existing layout methods face difficulties when dealing …
Visualizing large-scale spatial time series with geochron
In geo-related fields such as urban informatics, atmospheric science, and geography, large-
scale spatial time (ST) series (ie, geo-referred time series) are collected for monitoring and …
scale spatial time (ST) series (ie, geo-referred time series) are collected for monitoring and …
User-centered visual explorer of in-process comparison in spatiotemporal space
We propose a user-centered visual explorer (UcVE) for progressive comparing multiple
visualization units in spatiotemporal space. We create unique unit visualization with the …
visualization units in spatiotemporal space. We create unique unit visualization with the …
MepoGNN: Metapopulation epidemic forecasting with graph neural networks
Epidemic prediction is a fundamental task for epidemic control and prevention. Many
mechanistic models and deep learning models are built for this task. However, most …
mechanistic models and deep learning models are built for this task. However, most …
Metapopulation graph neural networks: Deep metapopulation epidemic modeling with human mobility
Epidemic prediction is a fundamental task for epidemic control and prevention. Many
mechanistic models and deep learning models are built for this task. However, most …
mechanistic models and deep learning models are built for this task. However, most …
Multilevel visual analysis of aggregate geo-networks
Numerous patterns found in urban phenomena, such as air pollution and human mobility,
can be characterized as many directed geospatial networks (geo-networks) that represent …
can be characterized as many directed geospatial networks (geo-networks) that represent …
Understanding railway usage behavior with ten million GPS records
Considering the essential role of public railway transport in urban planning and
development, it is crucial to understand railway travel behavior. With data and survey cost …
development, it is crucial to understand railway travel behavior. With data and survey cost …