PyTorch Geometric Temporal: Spatiotemporal Signal Processing with Neural Machine Learning Models (CIKM 2021)

This repository contains a reading list of papers on Time Series Forecasting/Prediction (TSF) and Spatio-Temporal Forecasting/Prediction (STF). These papers are mainly categorized according to the type of model.

Time-Series Work Summary in CS Top Conferences (NIPS, ICML, ICLR, KDD, AAAI, WWW, IJCAI, CIKM, ICDM, ICDE, etc.)

A Python package develop for transportation spatio-temporal big data processing, analysis and visualization.

Data visualization examples and tutorials from scratch. 数据可视化示例代码集与新手学习教程。

tsl: a PyTorch library for processing spatiotemporal data.

Traffic data processing tools in LibCity

ST-SSL (STSSL): Spatio-Temporal Self-Supervised Learning for Traffic Flow Forecasting/Prediction

A collection of research on spatio-temporal data mining

Paper & Code & Dataset Collection of Spatial-Temporal Data Mining.

A Python package for simple STAC queries

Organize some grid-based traffic flow datasets, mainly New York City bicycle and taxi data

A framework for Spatio-Temporal Data Analytics on Spark

Trajectory Mining Library

[CIKM'2023] "STExplainer: Explainable Spatio-Temporal Graph Neural Networks"

PDE-VAE: Variational Autoencoder for Extracting Interpretable Physical Parameters from Spatiotemporal Systems using Unsupervised Learning

Simple and effective tools for the analysis of movement data

A survey and paper list of current Spatio-Temporal Foundation Models from the pipeline perspective with awesome resources (paper, code, survey, etc.).

Graph Neural Networks utilization for Spatiotemporal graphs. These methods will be applied into the problem of forecasting traffic flow on PEMS-Bay, METR-LA and Seattle Loop Datasets

[CIKM'2023] "CL4ST: Spatio-Temporal Meta Contrastive Learning"