User Modeling and Personalization in Urban Computing
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Updated
Sep 17, 2019 - Jupyter Notebook
User Modeling and Personalization in Urban Computing
Repository for ''Contextualizing MLP-Mixers Spatiotemporally for Urban Data Forecast at Scale''
[CIKM'2024] "EasyST: A Simple Framework for Spatio-Temporal Prediction"
OpenAI-gym-like Reinforcement Learning environment for Dispatching of Mobile Chargers with SUMO. Compatible with Gym and popular RL libraries such as stable-baselines3.
Urban Computing 2021 Research Project @ Leiden University
Crowdsensing urban data in Africa
Search by string similarity an address from brazil south region
Prediction of trip duration in bicycle sharing systems using coarse-grained station representation
A professional list on Multi-modal Data Fusion Models and Key Datasets for Urban Computing.
Implementation of the spatialGAT in the paper: Spatial Attention Based Grid Representation Learning for Predicting Origin–Destination Flow (IEEE Big Data 2022)
Exploring UrbanAccess to determine walkability/transit accessibility in San Francisco and Waterloo
Official repository for the paper "Back to the Future: GNN-based NO2 Forecasting via Future Covariates" , IGARSS 2024
STCF: Spatial-Temporal Contrasting for Fine-Grained Urban Flow inference. IEEE Transactions on Big Data, 2023.
Urban Computing Foundation Charter
[CIKM'2023] "CL4ST: Spatio-Temporal Meta Contrastive Learning"
This repository contains source code implementation of projects for NTU's MSAI course AI6128 on Urban Computing (2020 Sem 1).
[ICML'2023] "GraphST: Spatial-Temporal Graph Learning with Adversarial Contrastive Adaptation"
[ICML'2024] "FlashST: A Simple and Universal Prompt-Tuning Framework for Traffic Prediction"
[ICDE'2023] When Spatio-Temporal Meet Wavelets: Disentangled Traffic Forecasting via Efficient Spectral Graph Attention Networks
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