tsinghua-fib-lab/Spatio-temporal-Diffusion-Point-Processes
A diffusion-based framework for spatio-temporal point processes
This project helps researchers and data scientists analyze and predict events that occur at specific times and locations, like earthquakes or disease outbreaks. It takes in historical spatio-temporal event data and outputs models that can simulate or forecast future event occurrences. This is designed for those in fields requiring predictive modeling of geographical and time-sensitive phenomena.
No commits in the last 6 months.
Use this if you need to model and predict the timing and location of discrete events over a geographical area, such as natural disasters, urban traffic patterns, or disease spread.
Not ideal if you're looking for real-time operational deployment without significant integration, or if your data doesn't involve distinct events with clear time and location stamps.
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Language
Python
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Last pushed
Mar 25, 2024
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