| iTransformer: Inverted Transformers Are Effective for Time Series Forecasting Y Liu, T Hu, H Zhang, H Wu, S Wang, L Ma, M Long International Conference on Learning Representations (ICLR 2024), 2023 | 601 | 2023 |
| Time-LLM: Time Series Forecasting by Reprogramming Large Language Models M Jin, S Wang, L Ma, Z Chu, JY Zhang, X Shi, PY Chen, Y Liang, YF Li, ... International Conference on Learning Representations (ICLR 2024), 2023 | 418 | 2023 |
| TimeMixer: Decomposable Multiscale Mixing for Time Series Forecasting S Wang, H Wu, X Shi, T Hu, H Luo, L Ma, JY Zhang, JUN ZHOU The Twelfth International Conference on Learning Representations (ICLR 2024), 2023 | 132 | 2023 |
| A meta reinforcement learning approach for predictive autoscaling in the cloud S Xue, C Qu, X Shi, C Liao, S Zhu, X Tan, L Ma, S Wang, S Wang, Y Hu, ... 28th ACM SIGKDD Int. Conf. on Knowledge Discovery & Data Mining (KDD 2022 …, 2022 | 42 | 2022 |
| A distributed PDP model based on spectral clustering for improving evaluation performance F Deng, J Lu, SY Wang, J Pan, LY Zhang World Wide Web (WWW) 22, 1555-1576, 2019 | 19 | 2019 |
| Establishment of attribute bitmaps for efficient XACML policy evaluation F Deng, S Wang, L Zhang, X Wei, J Yu Knowledge-Based Systems (KBS) 143, 93-101, 2018 | 19 | 2018 |
| Intelligent virtual assistants with llm-based process automation Y Guan, D Wang, Z Chu, S Wang, F Ni, R Song, L Li, J Gu, C Zhuang arXiv preprint arXiv:2312.06677, 2023 | 15 | 2023 |
| Intelligent Agents with LLM-based Process Automation Y Guan, D Wang, Z Chu, S Wang, F Ni, R Song, C Zhuang 30th ACM SIGKDD Int. Conf. on Knowledge Discovery & Data Mining (KDD 2024 …, 2024 | 13 | 2024 |
| A graph regularized point process model for event propagation sequence S Xue, X Shi, H Hao, L Ma, J Zhang, S Wang, S Wang 2021 International Joint Conference on Neural Networks (IJCNN), 1-7, 2021 | 11 | 2021 |
| End-to-end modeling of hierarchical time series using autoregressive transformer and conditional normalizing flow-based reconciliation S Wang, F Zhou, Y Sun, L Ma, J Zhang, Y Zheng 2022 IEEE International Conference on Data Mining (ICDM), 1087-1094, 2022 | 10 | 2022 |
| Time-MoE: Billion-Scale Time Series Foundation Models with Mixture of Experts X Shi, S Wang, Y Nie, D Li, Z Ye, Q Wen, M Jin International Conference on Learning Representations (ICLR 2025), 2024 | 8 | 2024 |
| Full scaling automation for sustainable development of green data centers S Wang, Y Sun, X Shi, S Zhu, LT Ma, J Zhang, Y Zheng, J Liu IJCAI 2023 Proceedings of the Thirty-Second International Joint Conference …, 2023 | 6 | 2023 |
| NeuralReconciler for Hierarchical Time Series Forecasting S Wang WSDM 2024 Proceedings of the 17th ACM International Conference on Web Search …, 2024 | 5 | 2024 |
| SLOTH: structured learning and task-based optimization for time series forecasting on hierarchies F Zhou, C Pan, L Ma, Y Liu, S Wang, J Zhang, X Zhu, X Hu, Y Hu, Y Zheng, ... Proceedings of the AAAI Conference on Artificial Intelligence 37 (9), 11417 …, 2023 | 4 | 2023 |
| TimeMixer++: A General Time Series Pattern Machine for Universal Predictive Analysis S Wang, J Li, X Shi, Z Ye, B Mo, W Lin, S Ju, Z Chu, M Jin International Conference on Learning Representations (ICLR 2025), 2024 | 3 | 2024 |
| Causal Interventional Prediction System for Robust and Explainable Effect Forecasting Z Chu, H Ding, G Zeng, S Wang, Y Li ACM International Conference on Information and Knowledge Management (CIKM 2024), 2024 | 2 | 2024 |
| Multiscale Representation Enhanced Temporal Flow Fusion Model for Long-Term Workload Forecasting S Wang, Z Chu, Y Sun, Y Liu, Y Guo, Y Chen, H Jian, L Ma, X Lu, J Zhou ACM International Conference on Information and Knowledge Management (CIKM 2024), 2024 | 2 | 2024 |
| Flow-Based End-to-End Model for Hierarchical Time Series Forecasting via Trainable Attentive-Reconciliation S Wang, Y Sun, Y Wang, F Zhou, LT Ma, J Zhang, YF Zheng DASFAA 2023 International Conference on Database Systems for Advanced …, 2023 | 2 | 2023 |
| Adaptive Two-Stage Cloud Resource Scaling via Hierarchical Multi-Indicator Forecasting and Bayesian Decision-Making Y Luo, S Wang, Z Yu, W Lu, X Gao, L Ma, G Chen arXiv preprint arXiv:2408.01000, 2024 | 1 | 2024 |
| Scaling to Billion Parameters for Time Series Foundation Models with Mixture of Experts X Shi, S Wang, Y Nie, D Li, Z Ye, Q Wen, M Jin NeurIPS Workshop on Time Series in the Age of Large Models, 2024 | | 2024 |
Zhixuan ChuAssociate Professor, Zhejiang University; Alibaba Group; Ant GroupE-mailová adresa ověřena na: alibaba-inc.com
