no code implementations • 6 Feb 2024 • Kethmi Hirushini Hettige, Jiahao Ji, Shili Xiang, Cheng Long, Gao Cong, Jingyuan Wang
Air quality prediction and modelling plays a pivotal role in public health and environment management, for individuals and authorities to make informed decisions.
1 code implementation • 21 Nov 2023 • Jiahao Ji, Wentao Zhang, Jingyuan Wang, Yue He, Chao Huang
It first encodes traffic data into two disentangled representations for associating invariant and variant ST contexts.
no code implementations • 16 Oct 2023 • Jiahao Ji, Jingyuan Wang, Yu Mou, Cheng Long
The framework consists of two main components: an automatic graph decomposition module that decomposes the original graph structure inherent in ST data into subgraphs corresponding to different factors, and a decomposed learning network that learns the partial ST data on each subgraph separately and integrates them for the final prediction.
1 code implementation • 7 Dec 2022 • Jiahao Ji, Jingyuan Wang, Chao Huang, Junjie Wu, Boren Xu, Zhenhe Wu, Junbo Zhang, Yu Zheng
ii) These models fail to capture the temporal heterogeneity induced by time-varying traffic patterns, as they typically model temporal correlations with a shared parameterized space for all time periods.
Ranked #1 on Traffic Prediction on BJTaxi
1 code implementation • 1 Sep 2022 • Jiahao Ji, Jingyuan Wang, Zhe Jiang, Jiawei Jiang, Hu Zhang
High-performance traffic flow prediction model designing, a core technology of Intelligent Transportation System, is a long-standing but still challenging task for industrial and academic communities.
Physics-informed machine learning Spatio-Temporal Forecasting +1