PyTorch Geometric Temporal: Spatiotemporal Signal Processing with Neural Machine Learning Models (CIKM 2021)
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Updated
Oct 14, 2024 - Python
PyTorch Geometric Temporal: Spatiotemporal Signal Processing with Neural Machine Learning Models (CIKM 2021)
A Python package develop for transportation spatio-temporal big data processing, analysis and visualization.
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 Python package for simple STAC queries
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
[CIKM'2023] "CL4ST: Spatio-Temporal Meta Contrastive Learning"
ST-OPTICS: Spatio-temporal clustering based on OPTICS
Spatio-temporal NHGIS Crosswalks
traffic flow prediction
This project evaluates ride-sharing algorithms on spatio-temporal data. The data in this case represents nearly 700 million trips in New York City.
Framework to build linked spatio-temporal data from vectorized evolutionary topographic map archives
Crowd flow prediction model
PurpleAirSF: datasets for realistic air quality forecasting
This repository contains de code and instructions to train the models and prepare the datasets for the experiments in the paper "Atom: Neural Traffic Compression with Spatio-Temporal Graph Neural Networks" accepted at the 2nd ACM CONEXT GNNet 2023 Workshop.
HISDAC-ES: Creating historical settlement data for Spain (1900-2020) based on cadastral building footprint data
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