DL-Traff: Survey and Benchmark of Deep Learning Models for Urban Traffic Prediction. - Renhe Jiang; Du Yin; Zhaonan Wang 001; Yizhuo Wang; Jiewen Deng; Hangchen Liu; Zekun Cai; Jinliang Deng; Xuan Song 001; Ryosuke Shibasaki (CIKM, 2021)

ST-Norm: Spatial and Temporal Normalization for Multi-variate Time Series Forecasting. - Jinliang Deng; Xiusi Chen; Renhe Jiang; Xuan Song 001; Ivor W. Tsang (KDD, 2021)

The Pulse of Urban Transport: Exploring the Co-evolving Pattern for Spatio-temporal Forecasting. - Jinliang Deng; Xiusi Chen; Zipei Fan; Renhe Jiang; Xuan Song 001; Ivor W. Tsang (ACM Trans. Knowl. Discov. Data, 2021)

Heterogeneous Hypergraph Neural Network for Friend Recommendation with Human Mobility. - Yongkang Li 002; Zipei Fan; Jixiao Zhang; Dengheng Shi; Tianqi Xu; Du Yin; Jinliang Deng; Xuan Song 001 (CIKM, 2022)

Spatio-Temporal Adaptive Embedding Makes Vanilla Transformer SOTA for Traffic Forecasting. - Hangchen Liu; Zheng Dong 006; Renhe Jiang; Jiewen Deng; Jinliang Deng; Quanjun Chen; Xuan Song 001 (CIKM, 2023)

Learning Gaussian Mixture Representations for Tensor Time Series Forecasting. - Jiewen Deng; Jinliang Deng; Renhe Jiang; Xuan Song 001 (IJCAI, 2023)

Drift: Fine-Grained Prediction of the Co-Evolution of Production and Test Code via Machine Learning. - Lei Liu; Sinan Wang; Yepang Liu 001; Jinliang Deng; Sicen Liu (Internetware, 2023)

Gotta: Generative Few-shot Question Answering by Prompt-based Cloze Data Augmentation. - Xiusi Chen; Yu Zhang 044; Jinliang Deng; Jyun-Yu Jiang; Wei Wang 010 (SDM, 2023)

Learning Structured Components: Towards Modular and Interpretable Multivariate Time Series Forecasting. - Jinliang Deng; Xiusi Chen; Renhe Jiang; Du Yin; Yi Yang 001; Xuan Song 001; Ivor W. Tsang (CoRR, 2023)

STAEformer: Spatio-Temporal Adaptive Embedding Makes Vanilla Transformer SOTA for Traffic Forecasting. - Hangchen Liu; Zheng Dong 006; Renhe Jiang; Jiewen Deng; Jinliang Deng; Quanjun Chen; Xuan Song 001 (CoRR, 2023)

Spatio-Temporal-Decoupled Masked Pre-training: Benchmarked on Traffic Forecasting. - Haotian Gao; Renhe Jiang; Zheng Dong 006; Jinliang Deng; Yuxin Ma; Xuan Song 001 (CoRR, 2023)

HMGCL: Heterogeneous multigraph contrastive learning for LBSN friend recommendation. - Yongkang Li 002; Zipei Fan; Du Yin; Renhe Jiang; Jinliang Deng; Xuan Song 001 (World Wide Web (WWW), 2023)

A Multi-View Multi-Task Learning Framework for Multi-Variate Time Series Forecasting. - Jinliang Deng; Xiusi Chen; Renhe Jiang; Xuan Song 001; Ivor W. Tsang (IEEE Trans. Knowl. Data Eng., 2023)

Enhancing Spatio-temporal Quantile Forecasting with Curriculum Learning: Lessons Learned. - Du Yin; Jinliang Deng; Shuang Ao; Zechen Li; Hao Xue 001; Arian Prabowo; Renhe Jiang; Xuan Song 001; Flora D. Salim (SIGSPATIAL/GIS, 2024)

Spatial-Temporal-Decoupled Masked Pre-training for Spatiotemporal Forecasting. - Haotian Gao; Renhe Jiang; Zheng Dong 006; Jinliang Deng; Yuxin Ma; Xuan Song 001 (IJCAI, 2024)

Heterogeneity-Informed Meta-Parameter Learning for Spatiotemporal Time Series Forecasting. - Zheng Dong 006; Renhe Jiang; Haotian Gao; Hangchen Liu; Jinliang Deng; Qingsong Wen; Xuan Song 001 (KDD, 2024)

Parsimony or Capability? Decomposition Delivers Both in Long-term Time Series Forecasting. - Jinliang Deng; Feiyang Ye 001; Du Yin; Xuan Song 001; Ivor W. Tsang; Hui Xiong 001 (NeurIPS, 2024)

The Bigger the Better? Rethinking the Effective Model Scale in Long-term Time Series Forecasting. - Jinliang Deng; Xuan Song 001; Ivor W. Tsang; Hui Xiong 001 (CoRR, 2024)

Disentangling Structured Components: Towards Adaptive, Interpretable and Scalable Time Series Forecasting. - Jinliang Deng; Xiusi Chen; Renhe Jiang; Du Yin; Yi Yang 001; Xuan Song 001; Ivor W. Tsang (IEEE Trans. Knowl. Data Eng., 2024)

TTS-Norm: Forecasting Tensor Time Series via Multi-Way Normalization. - Jiewen Deng; Jinliang Deng; Du Yin; Renhe Jiang; Xuan Song 001 (ACM Trans. Knowl. Discov. Data, 2024)

Accurate and Efficient Multivariate Time Series Forecasting via Offline Clustering. - Yiming Niu; Jinliang Deng; Lulu Zhang; Zimu Zhou; Yongxin Tong (ICDE, 2025)

AutoSTF: Decoupled Neural Architecture Search for Cost-Effective Automated Spatio-Temporal Forecasting. - Tengfei Lyu; Weijia Zhang 003; Jinliang Deng; Hao Liu 026 (KDD (1), 2025)

FANformer: Improving Large Language Models Through Effective Periodicity Modeling. - Yihong Dong; Ge Li 001; Xue Jiang; Yongding Tao; Kechi Zhang; Hao Zhu; Huanyu Liu; Jiazheng Ding; Jia Li 012; Jinliang Deng; Hong Mei 001 (CoRR, 2025)