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2020 – today
- 2025
[c14]Yiming Niu, Jinliang Deng, Lulu Zhang, Zimu Zhou, Yongxin Tong:
Accurate and Efficient Multivariate Time Series Forecasting via Offline Clustering. ICDE 2025: 3056-3069- [c13]Min Yang, Yang An, Jinliang Deng, Xiaoyu Li, Bin Xu, Ji Zhong, Xiankai Lu, Yongshun Gong:
CAN-ST: Clustering Adaptive Normalization for Spatio-temporal OOD Learning. IJCAI 2025: 3543-3551 - [c12]Tengfei Lyu
, Weijia Zhang, Jinliang Deng, Hao Liu:
AutoSTF: Decoupled Neural Architecture Search for Cost-Effective Automated Spatio-Temporal Forecasting. KDD (1) 2025: 985-996 - [i14]Yihong Dong, Ge Li, Xue Jiang, Yongding Tao, Kechi Zhang, Hao Zhu, Huanyu Liu, Jiazheng Ding, Jia Li, Jinliang Deng, Hong Mei:
FANformer: Improving Large Language Models Through Effective Periodicity Modeling. CoRR abs/2502.21309 (2025) - [i13]Yiming Niu, Jinliang Deng, Lulu Zhang, Zimu Zhou, Yongxin Tong:
Accurate and Efficient Multivariate Time Series Forecasting via Offline Clustering. CoRR abs/2505.05738 (2025) - [i12]Yiming Niu, Jinliang Deng, Yongxin Tong:
PhaseFormer: From Patches to Phases for Efficient and Effective Time Series Forecasting. CoRR abs/2510.04134 (2025) - 2024
- [j5]Jiewen Deng, Jinliang Deng, Du Yin, Renhe Jiang, Xuan Song:
TTS-Norm: Forecasting Tensor Time Series via Multi-Way Normalization. ACM Trans. Knowl. Discov. Data 18(1): 3:1-3:25 (2024) - [j4]Jinliang Deng, Xiusi Chen, Renhe Jiang, Du Yin, Yi Yang, Xuan Song, Ivor W. Tsang:
Disentangling Structured Components: Towards Adaptive, Interpretable and Scalable Time Series Forecasting. IEEE Trans. Knowl. Data Eng. 36(8): 3783-3800 (2024) - [c11]Du Yin, Jinliang Deng, Shuang Ao, Zechen Li, Hao Xue, Arian Prabowo, Renhe Jiang, Xuan Song, Flora D. Salim:
Enhancing Spatio-temporal Quantile Forecasting with Curriculum Learning: Lessons Learned. SIGSPATIAL/GIS 2024: 42-53 - [c10]Haotian Gao, Renhe Jiang, Zheng Dong, Jinliang Deng, Yuxin Ma, Xuan Song:
Spatial-Temporal-Decoupled Masked Pre-training for Spatiotemporal Forecasting. IJCAI 2024: 3998-4006 - [c9]Zheng Dong, Renhe Jiang, Haotian Gao, Hangchen Liu, Jinliang Deng, Qingsong Wen, Xuan Song:
Heterogeneity-Informed Meta-Parameter Learning for Spatiotemporal Time Series Forecasting. KDD 2024: 631-641 - [c8]Jinliang Deng, Feiyang Ye, Du Yin, Xuan Song, Ivor W. Tsang, Hui Xiong:
Parsimony or Capability? Decomposition Delivers Both in Long-term Time Series Forecasting. NeurIPS 2024 - [i11]Jinliang Deng, Xuan Song, Ivor W. Tsang, Hui Xiong:
The Bigger the Better? Rethinking the Effective Model Scale in Long-term Time Series Forecasting. CoRR abs/2401.11929 (2024) - [i10]Zheng Dong, Renhe Jiang, Haotian Gao, Hangchen Liu, Jinliang Deng, Qingsong Wen, Xuan Song:
Heterogeneity-Informed Meta-Parameter Learning for Spatiotemporal Time Series Forecasting. CoRR abs/2405.10800 (2024) - [i9]Du Yin, Jinliang Deng, Shuang Ao, Zechen Li, Hao Xue, Arian Prabowo, Renhe Jiang, Xuan Song, Flora D. Salim:
Enhancing Spatio-temporal Quantile Forecasting with Curriculum Learning: Lessons Learned. CoRR abs/2406.12709 (2024) - [i8]Tengfei Lyu, Weijia Zhang, Jinliang Deng, Hao Liu:
AutoSTF: Decoupled Neural Architecture Search for Cost-Effective Automated Spatio-Temporal Forecasting. CoRR abs/2409.16586 (2024) - 2023
- [j3]Jinliang Deng, Xiusi Chen, Renhe Jiang, Xuan Song, Ivor W. Tsang:
A Multi-View Multi-Task Learning Framework for Multi-Variate Time Series Forecasting. IEEE Trans. Knowl. Data Eng. 35(8): 7665-7680 (2023) - [j2]Yongkang Li, Zipei Fan, Du Yin, Renhe Jiang, Jinliang Deng, Xuan Song:
HMGCL: Heterogeneous multigraph contrastive learning for LBSN friend recommendation. World Wide Web (WWW) 26(4): 1625-1648 (2023) - [c7]Hangchen Liu, Zheng Dong, Renhe Jiang, Jiewen Deng, Jinliang Deng, Quanjun Chen, Xuan Song:
Spatio-Temporal Adaptive Embedding Makes Vanilla Transformer SOTA for Traffic Forecasting. CIKM 2023: 4125-4129 - [c6]Jiewen Deng, Jinliang Deng, Renhe Jiang, Xuan Song:
Learning Gaussian Mixture Representations for Tensor Time Series Forecasting. IJCAI 2023: 2077-2085 - [c5]Lei Liu, Sinan Wang, Yepang Liu, Jinliang Deng, Sicen Liu:
Drift: Fine-Grained Prediction of the Co-Evolution of Production and Test Code via Machine Learning. Internetware 2023: 227-237 - [c4]Xiusi Chen, Yu Zhang, Jinliang Deng, Jyun-Yu Jiang, Wei Wang:
Gotta: Generative Few-shot Question Answering by Prompt-based Cloze Data Augmentation. SDM 2023: 909-917 - [i7]Jinliang Deng, Xiusi Chen, Renhe Jiang, Du Yin, Yi Yang, Xuan Song, Ivor W. Tsang:
Learning Structured Components: Towards Modular and Interpretable Multivariate Time Series Forecasting. CoRR abs/2305.13036 (2023) - [i6]Jiewen Deng, Jinliang Deng, Renhe Jiang, Xuan Song:
Learning Gaussian Mixture Representations for Tensor Time Series Forecasting. CoRR abs/2306.00390 (2023) - [i5]Xiusi Chen, Yu Zhang, Jinliang Deng, Jyun-Yu Jiang, Wei Wang:
Gotta: Generative Few-shot Question Answering by Prompt-based Cloze Data Augmentation. CoRR abs/2306.04101 (2023) - [i4]Hangchen Liu, Zheng Dong, Renhe Jiang, Jiewen Deng, Jinliang Deng, Quanjun Chen, Xuan Song:
STAEformer: Spatio-Temporal Adaptive Embedding Makes Vanilla Transformer SOTA for Traffic Forecasting. CoRR abs/2308.10425 (2023) - [i3]Haotian Gao, Renhe Jiang, Zheng Dong, Jinliang Deng, Yuxin Ma, Xuan Song:
Spatio-Temporal-Decoupled Masked Pre-training: Benchmarked on Traffic Forecasting. CoRR abs/2312.00516 (2023) - 2022
- [c3]Yongkang Li, Zipei Fan, Jixiao Zhang, Dengheng Shi, Tianqi Xu, Du Yin, Jinliang Deng, Xuan Song:
Heterogeneous Hypergraph Neural Network for Friend Recommendation with Human Mobility. CIKM 2022: 4209-4213 - 2021
- [j1]Jinliang Deng, Xiusi Chen, Zipei Fan, Renhe Jiang, Xuan Song, Ivor W. Tsang:
The Pulse of Urban Transport: Exploring the Co-evolving Pattern for Spatio-temporal Forecasting. ACM Trans. Knowl. Discov. Data 15(6): 103:1-103:25 (2021) - [c2]Renhe Jiang, Du Yin, Zhaonan Wang, Yizhuo Wang, Jiewen Deng, Hangchen Liu, Zekun Cai, Jinliang Deng, Xuan Song, Ryosuke Shibasaki:
DL-Traff: Survey and Benchmark of Deep Learning Models for Urban Traffic Prediction. CIKM 2021: 4515-4525 - [c1]Jinliang Deng, Xiusi Chen, Renhe Jiang, Xuan Song, Ivor W. Tsang:
ST-Norm: Spatial and Temporal Normalization for Multi-variate Time Series Forecasting. KDD 2021: 269-278 - [i2]Renhe Jiang, Du Yin, Zhaonan Wang, Yizhuo Wang, Jiewen Deng, Hangchen Liu, Zekun Cai, Jinliang Deng, Xuan Song, Ryosuke Shibasaki:
DL-Traff: Survey and Benchmark of Deep Learning Models for Urban Traffic Prediction. CoRR abs/2108.09091 (2021) - [i1]Jinliang Deng, Xiusi Chen, Renhe Jiang, Xuan Song, Ivor W. Tsang:
A Multi-view Multi-task Learning Framework for Multi-variate Time Series Forecasting. CoRR abs/2109.01657 (2021)
Coauthor Index
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