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AutoSTG: Neural Architecture Search for Predictions of Spatio-Temporal Graph

WWW 2021

Fine-grained Urban Flow Prediction

WWW 2021

Traffic Flow Forecasting with Spatial-Temporal Graph Diffusion Network

AAAI 2021

You Are How You Use: Catching Gas Theft Suspects among Diverse Restaurant Users

CIKM 2020, Applied Research Track

AutoST: Efficient Neural Architecture Search for Spatio-Temporal Prediction

[ORAL] KDD 2020, Research Track (acceptance rate: 16.8%)

Revisiting Convolutional Neural Networks for Citywide Crowd Flow Analytics

ECML-PKDD 2020

CityGuard: Citywide Fire Risk Forecasting Using A Machine Learning Approach

UbiComp 2020

Matrix Factorization for Spatio-Temporal Neural Networks with Applications to Urban Flow Prediction

CIKM 2019, Applied Research Track (acceptance rate: 21.8%)

CityTraffic: Modeling Citywide Traffic via Neural Memorization and Generalization Approach

CIKM 2019, Applied Research Track (acceptance rate: 21.8%)

Urban Traffic Prediction from Spatio-Temporal Data using Deep Meta Learning

[ORAL] KDD 2019, Research Track (acceptance rate: 14.2%)