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.
PyTorch Geometric Temporal: Spatiotemporal Signal Processing with Neural Machine Learning Models (CIKM 2021)
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 survey and paper list of current Spatio-Temporal Foundation Models from the pipeline perspective with awesome resources (paper, code, survey, etc.).
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
[CIKM'2023] "STExplainer: Explainable Spatio-Temporal Graph Neural Networks"
[ACM TIST] "LLM4Urban: Urban Computing in the Era of Large Language Models"
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
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
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