AaltoPML/spatiotemporal-graph-kernels
The official implementation of Non-separable Spatio-temporal Graph Kernels via SPDEs.
This project helps researchers and data scientists analyze complex data that changes over both space and time, such as disease spread or heat transfer. You provide historical spatio-temporal data on a network or graph, and the tool helps you predict future trends or fill in missing data points by capturing how events interact across locations and moments. This is for professionals modeling dynamic systems where both location and time play a crucial role.
No commits in the last 6 months.
Use this if you need to accurately model phenomena like disease outbreaks, information propagation, or environmental changes that evolve across a network of interconnected locations over time.
Not ideal if your data doesn't have a clear spatial or network structure, or if the 'time' aspect of your data is not crucial to its underlying interactions.
Stars
16
Forks
2
Language
Python
License
Apache-2.0
Category
Last pushed
Jun 02, 2022
Commits (30d)
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