GeoMAN: Multi-level Attention Networks for Geo-sensory Time Series Prediction. - Yuxuan Liang; Songyu Ke; Junbo Zhang; Xiuwen Yi; Yu Zheng 004 (IJCAI, 2018)

Robust Spatio-Temporal Purchase Prediction via Deep Meta Learning. - Huiling Qin; Songyu Ke; Xiaodu Yang; Haoran Xu 003; Xianyuan Zhan; Yu Zheng 004 (AAAI, 2021)

AutoSTG: Neural Architecture Search for Predictions of Spatio-Temporal Graph✱. - Zheyi Pan; Songyu Ke; Xiaodu Yang; Yuxuan Liang; Yong Yu 001; Junbo Zhang; Yu Zheng 004 (WWW, 2021)

Efficient Spatio-Temporal Randomly Wired Neural Networks for Traffic Forecasting. - Li Song; Kainan Bao; Songyu Ke; Chunyang Li 001; Junbo Zhang; Yu Zheng 004 (ICDM (Workshops), 2022)

Gas-Theft Suspect Detection Among Boiler Room Users: A Data-Driven Approach. - Xiuwen Yi; Xiaodu Yang; Yanyong Huang; Songyu Ke; Junbo Zhang; Tianrui Li 001; Yu Zheng 004 (IEEE Trans. Knowl. Data Eng., 2022)

AirFormer: Predicting Nationwide Air Quality in China with Transformers. - Yuxuan Liang; Yutong Xia; Songyu Ke; Yiwei Wang 001; Qingsong Wen; Junbo Zhang; Yu Zheng 004; Roger Zimmermann (AAAI, 2023)

Spatio-Temporal Contrastive Self-Supervised Learning for POI-level Crowd Flow Inference. - Songyu Ke; Ting Li; Li Song; Yanping Sun; Qintian Sun; Junbo Zhang; Yu Zheng (CoRR, 2023)

AutoSTG+: An automatic framework to discover the optimal network for spatio-temporal graph prediction. - Songyu Ke; Zheyi Pan; Tianfu He; Yuxuan Liang; Junbo Zhang; Yu Zheng 004 (Artif. Intell., 2023)

GSDI: Spatio-Temporal Contrastive Learning for Geo-Sensory Data Inference. - Songyu Ke; Yuxuan Liang; Xiuwen Yi; Junbo Zhang; Yu Zheng 004 (IJCNN, 2024)

VQGG: Generating Adaptive Graphs for Traffic Forecasting via a Vector-Quantized Graph Generator. - Songyu Ke; Chenyu Wu; Jinjin Guo; Junbo Zhang; Yu Zheng (IJCNN, 2024)

GeoMAE: Masking Representation Learning for Spatio-Temporal Graph Forecasting with Missing Values. - Songyu Ke; Chenyu Wu; Yuxuan Liang; Xiuwen Yi; Yanping Sun; Junbo Zhang; Yu Zheng 004 (CoRR, 2025)