https://github.com/1lmao/deepstpp-with-mambassm
Spatial analysis using Deep Spatio Temporal Point Process (DeepSTPP) updated with state-of-the-art mamba state space model, using spatiotemporal Hawkes Process, spatiotemporal self-correcting process, NJ COVID-19 and Japanese earthquake data.
https://github.com/1lmao/deepstpp-with-mambassm
encoder-decoder hawkes-process mamba neural-spatiotemporal-point-process neural-temporal-point-processes recurrent-marked-temporal-point-process recurrent-neural-networks self-correcting-point-process spatial-ai spatial-analysis spatio-temporal spatiotemporal spatiotemporal-hawkes-process spatiotemporal-self-correcting-process structured-state-space-models structured-state-space-sequence-model transformer
Last synced: 3 months ago
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Spatial analysis using Deep Spatio Temporal Point Process (DeepSTPP) updated with state-of-the-art mamba state space model, using spatiotemporal Hawkes Process, spatiotemporal self-correcting process, NJ COVID-19 and Japanese earthquake data.
- Host: GitHub
- URL: https://github.com/1lmao/deepstpp-with-mambassm
- Owner: 1lmao
- License: mit
- Created: 2025-06-07T20:37:21.000Z (5 months ago)
- Default Branch: main
- Last Pushed: 2025-06-08T01:55:41.000Z (5 months ago)
- Last Synced: 2025-07-08T14:43:39.142Z (4 months ago)
- Topics: encoder-decoder, hawkes-process, mamba, neural-spatiotemporal-point-process, neural-temporal-point-processes, recurrent-marked-temporal-point-process, recurrent-neural-networks, self-correcting-point-process, spatial-ai, spatial-analysis, spatio-temporal, spatiotemporal, spatiotemporal-hawkes-process, spatiotemporal-self-correcting-process, structured-state-space-models, structured-state-space-sequence-model, transformer
- Language: Python
- Homepage:
- Size: 20.1 MB
- Stars: 3
- Watchers: 0
- Forks: 0
- Open Issues: 0