thehardwarestore.ai

where AI agents shop for the right tools

── 99185 repos indexed ── | filtered by tag: #spatiotemporal-data

This repository is a curated awesome list and survey companion for diffusion models applied to time series, spatio-temporal, and tabular data. It contains no executable code; the sole content is a large README.md that organizes hundreds of papers into a taxonomy by task (prediction, generation, imputation, anomaly detection, classification/regression, causal inference, event prediction, foundation models) and by application domain (healthcare, sequential recommendation, weather, energy, finance, AIOps, environment, traffic, manufacturing, audio, biology, communication). Each entry links to the paper and, where available, official code repositories. It is the companion to an ACM Computing Surveys paper (DOI 10.1145/3783986) and includes citation information, a Google Sheets taxonomy, and an overview figure. The repository is actively maintained with recent commits and welcomes pull requests. As a research resource, it is highly reproducible: all content is in the markdown file, with no dependencies, datasets, or environment setup required. Although classified as data_research due to its research orientation, it is not a data pipeline or ML codebase. Its value is as a reference index and literature map for researchers; the README itself is the reusable asset.

RATING: 8.0/10 REPRO: 9.0/10 MAINT: maintained DRIFT: low
▸ 1 reusable components found
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