{"id":19199833,"url":"https://github.com/rose-stl-lab/autostpp","last_synced_at":"2026-03-05T02:32:14.258Z","repository":{"id":201965428,"uuid":"546826088","full_name":"Rose-STL-Lab/AutoSTPP","owner":"Rose-STL-Lab","description":"Automatic Integration for Neural Spatio-Temporal Point Process models (AI-STPP) is a new paradigm for exact, efficient, non-parametric inference of point process. 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Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"\u003cp align=\"center\" \u003e\n  \u003ca href=\"https://github.com/Rose-STL-Lab/AI-STPP\"\u003e\u003cimg src=\"https://raw.githubusercontent.com/Rose-STL-Lab/AutoSTPP/refs/heads/main/Auto-STPP.png\" width=\"256\" height=\"256\" alt=\"AI-STPP\"\u003e\u003c/a\u003e\n\u003c/p\u003e\n\u003ch1 align=\"center\"\u003eAuto-STPP\u003c/h1\u003e\n\u003ch4 align=\"center\"\u003e✨Automatic Integration for Neural Spatiotemporal Point Process✨\u003c/h4\u003e\n\n\u003cp align=\"center\"\u003e\n    \u003ca href=\"https://raw.githubusercontent.com/Rose-STL-Lab/AutoSTPP/refs/heads/main/LICENSE\"\u003e\u003cimg src=\"https://img.shields.io/badge/License-MIT-yellow.svg\" alt=\"license\"\u003e\u003c/a\u003e\n    \u003cimg src=\"https://img.shields.io/badge/Python-3.10+-yellow\" alt=\"python\"\u003e\n    \u003cimg src=\"https://img.shields.io/badge/Version-1.1.0-green\" alt=\"version\"\u003e\n\u003c/p\u003e\n\n## | Introduction\n\n**Auto**matic Integration for Neural **S**patio-**T**emporal **P**oint **P**rocess models (Auto-STPP) is a new paradigm for exact, efficient, non-parametric inference of spatiotemporal point process.\n\n## | Citation\n\n[[2310.06179] Automatic Integration for Spatiotemporal Neural Point Processes](https://arxiv.org/abs/2310.06179)\n\n```\n@article{zhou2023automatic,\n  title={Automatic Integration for Spatiotemporal Neural Point Processes},\n  author={Zhou, Zihao and Yu, Rose},\n  journal={arXiv preprint arXiv:2310.06179},\n  year={2023}\n}\n```\n\n## | Installation\n\nDependencies: `make`, `conda-lock`\n\n```bash\nmake create_environment\nconda activate autoint-stpp\n```\n\n## | Dataset Download\n\n```bash\npython src/download_data.py\n```\n\n## | Training and Testing\n\nSpecify the parameters in `configs/autoint_stpp.yaml` and then run\n\n```bash\nmake run_stpp config=autoint_stpp\n```\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Frose-stl-lab%2Fautostpp","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Frose-stl-lab%2Fautostpp","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Frose-stl-lab%2Fautostpp/lists"}