UrbanGPT: Spatio-Temporal Large Language Models

1 code implementation • 25 Feb 2024 • Zhonghang Li, Lianghao Xia, Jiabin Tang, Yong Xu, Lei Shi, Long Xia, Dawei Yin, Chao Huang

These findings highlight the potential of building large language models for spatio-temporal learning, particularly in zero-shot scenarios where labeled data is scarce.

GPT-ST: Generative Pre-Training of Spatio-Temporal Graph Neural Networks

1 code implementation • NeurIPS 2023 • Zhonghang Li, Lianghao Xia, Yong Xu, Chao Huang

This strategy guides the mask autoencoder in learning robust spatio-temporal representations and facilitates the modeling of different relationships, ranging from intra-cluster to inter-cluster, in an easy-to-hard training manner.

Automated Spatio-Temporal Graph Contrastive Learning

1 code implementation • 6 May 2023 • Qianru Zhang, Chao Huang, Lianghao Xia, Zheng Wang, Zhonghang Li, SiuMing Yiu

In this paper, we tackle the above challenges by exploring the Automated Spatio-Temporal graph contrastive learning paradigm (AutoST) over the heterogeneous region graph generated from multi-view data sources.

Contrastive Learning

Spatial-Temporal Hypergraph Self-Supervised Learning for Crime Prediction

1 code implementation • 18 Apr 2022 • Zhonghang Li, Chao Huang, Lianghao Xia, Yong Xu, Jian Pei

Crime has become a major concern in many cities, which calls for the rising demand for timely predicting citywide crime occurrence.

Crime Prediction Decision Making +1