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ORCIDTian Zhou 0004
Person information
- affiliation: Alibaba Group, DAMO Academy, Hangzhou, China
- affiliation (PhD 2016): Rutgers University, Department of Chemistry and Chemical Biology, New Brunswick, NJ, USA
Other persons with the same name
- Tian Zhou — disambiguation page
- Tian Zhou 0001
![[0000-0001-6423-4090]](https://dblp.dagstuhl.de/img/orcid-mark.12x12.png "0000-0001-6423-4090")
— Purdue University, Lyles School of Civil Engineering, IN, USA - Tian Zhou 0002 — Harbin Engineering University, Acoustic Science and Technology Laboratory, China
- Tian Zhou 0003 — Xi'an Jiaotong University, Department of Computer Science and Technology, China (and 1 more)
- Tian Zhou 0005 — Purdue University, School of Industrial Engineering, West Lafayette, IN, USA (and 1 more)
- Tian Zhou 0006 — Verizon Media, Yahoo Research, Sunnyvale, CA, USA
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2020 – today
- 2025
[c16]Yaxuan Kong, Zepu Wang, Yuqi Nie, Tian Zhou, Stefan Zohren, Yuxuan Liang, Peng Sun, Qingsong Wen:
Unlocking the Power of LSTM for Long Term Time Series Forecasting. AAAI 2025: 11968-11976- 2024
- [j2]Xue Wang, Tian Zhou, Jianqing Zhu, Jialin Liu, Kun Yuan, Tao Yao, Wotao Yin, Rong Jin, HanQin Cai:
S$^\text{3}$Attention: Improving Long Sequence Attention With Smoothed Skeleton Sketching. IEEE J. Sel. Top. Signal Process. 18(6): 985-996 (2024) - [c15]Xue Wang, Tian Zhou, Qingsong Wen, Jinyang Gao, Bolin Ding, Rong Jin:
CARD: Channel Aligned Robust Blend Transformer for Time Series Forecasting. ICLR 2024 - [c14]Ziqing Ma, Wenwei Wang, Tian Zhou, Chao Chen, Bingqing Peng, Liang Sun, Rong Jin:
FusionSF: Fuse Heterogeneous Modalities in a Vector Quantized Framework for Robust Solar Power Forecasting. KDD 2024: 5532-5543 - [i21]Peisong Niu, Tian Zhou, Xue Wang, Liang Sun, Rong Jin:
Attention as Robust Representation for Time Series Forecasting. CoRR abs/2402.05370 (2024) - [i20]Ziqing Ma, Wenwei Wang, Tian Zhou, Chao Chen, Bingqing Peng, Liang Sun, Rong Jin:
FusionSF: Fuse Heterogeneous Modalities in a Vector Quantized Framework for Robust Solar Power Forecasting. CoRR abs/2402.05823 (2024) - [i19]Yanjun Zhao, Tian Zhou, Chao Chen, Liang Sun, Yi Qian, Rong Jin:
Sparse-VQ Transformer: An FFN-Free Framework with Vector Quantization for Enhanced Time Series Forecasting. CoRR abs/2402.05830 (2024) - [i18]Xue Wang, Tian Zhou, Jianqing Zhu, Jialin Liu, Kun Yuan, Tao Yao, Wotao Yin, Rong Jin, HanQin Cai:
S3Attention: Improving Long Sequence Attention with Smoothed Skeleton Sketching. CoRR abs/2408.08567 (2024) - [i17]Yaxuan Kong, Zepu Wang, Yuqi Nie, Tian Zhou, Stefan Zohren, Yuxuan Liang, Peng Sun, Qingsong Wen:
Unlocking the Power of LSTM for Long Term Time Series Forecasting. CoRR abs/2408.10006 (2024) - [i16]Yangyang Guo, Yanjun Zhao, Sizhe Dang, Tian Zhou, Liang Sun, Yi Qian:
Less is more: Embracing sparsity and interpolation with Esiformer for time series forecasting. CoRR abs/2410.05726 (2024) - [i15]Peiyuan Liu, Tian Zhou, Liang Sun, Rong Jin:
Mitigating Time Discretization Challenges with WeatherODE: A Sandwich Physics-Driven Neural ODE for Weather Forecasting. CoRR abs/2410.06560 (2024) - 2023
- [j1]Zhaoyang Zhu, Weiqi Chen, Rui Xia, Tian Zhou, Peisong Niu, Bingqing Peng, Wenwei Wang, Hengbo Liu, Ziqing Ma, Xinyue Gu, Jin Wang, Qiming Chen, Linxiao Yang, Qingsong Wen, Liang Sun:
Energy forecasting with robust, flexible, and explainable machine learning algorithms. AI Mag. 44(4): 377-393 (2023) - [c13]Zhaoyang Zhu, Weiqi Chen, Rui Xia, Tian Zhou, Peisong Niu, Bingqing Peng, Wenwei Wang, Hengbo Liu, Ziqing Ma, Qingsong Wen, Liang Sun:
eForecaster: Unifying Electricity Forecasting with Robust, Flexible, and Explainable Machine Learning Algorithms. AAAI 2023: 15630-15638 - [c12]Yanjun Zhao, Ziqing Ma, Tian Zhou, Mengni Ye, Liang Sun, Yi Qian:
GCformer: An Efficient Solution for Accurate and Scalable Long-Term Multivariate Time Series Forecasting. CIKM 2023: 3464-3473 - [c11]Hengbo Liu, Ziqing Ma, Linxiao Yang, Tian Zhou, Rui Xia, Yi Wang, Qingsong Wen, Liang Sun:
SADI: A Self-Adaptive Decomposed Interpretable Framework for Electric Load Forecasting Under Extreme Events. ICASSP 2023: 1-5 - [c10]Qingsong Wen, Tian Zhou, Chaoli Zhang, Weiqi Chen, Ziqing Ma, Junchi Yan, Liang Sun:
Transformers in Time Series: A Survey. IJCAI 2023: 6778-6786 - [c9]Yiyuan Yang, Chaoli Zhang, Tian Zhou, Qingsong Wen, Liang Sun:
DCdetector: Dual Attention Contrastive Representation Learning for Time Series Anomaly Detection. KDD 2023: 3033-3045 - [c8]Tian Zhou, Peisong Niu, Xue Wang, Liang Sun, Rong Jin:
One Fits All: Power General Time Series Analysis by Pretrained LM. NeurIPS 2023 - [i14]Tian Zhou, Peisong Niu, Xue Wang, Liang Sun, Rong Jin:
Power Time Series Forecasting by Pretrained LM. CoRR abs/2302.11939 (2023) - [i13]Ming Jin, Guangsi Shi, Yuan-Fang Li, Qingsong Wen, Bo Xiong, Tian Zhou, Shirui Pan:
How Expressive are Spectral-Temporal Graph Neural Networks for Time Series Forecasting? CoRR abs/2305.06587 (2023) - [i12]Xue Wang, Tian Zhou, Qingsong Wen, Jinyang Gao, Bolin Ding, Rong Jin:
Make Transformer Great Again for Time Series Forecasting: Channel Aligned Robust Dual Transformer. CoRR abs/2305.12095 (2023) - [i11]Hengbo Liu, Ziqing Ma, Linxiao Yang, Tian Zhou, Rui Xia, Yi Wang, Qingsong Wen, Liang Sun:
SaDI: A Self-adaptive Decomposed Interpretable Framework for Electric Load Forecasting under Extreme Events. CoRR abs/2306.08299 (2023) - [i10]Yanjun Zhao, Ziqing Ma, Tian Zhou, Liang Sun, Mengni Ye, Yi Qian:
GCformer: An Efficient Framework for Accurate and Scalable Long-Term Multivariate Time Series Forecasting. CoRR abs/2306.08325 (2023) - [i9]Yiyuan Yang, Chaoli Zhang, Tian Zhou, Qingsong Wen, Liang Sun:
DCdetector: Dual Attention Contrastive Representation Learning for Time Series Anomaly Detection. CoRR abs/2306.10347 (2023) - [i8]Tian Zhou, Peisong Niu, Xue Wang, Liang Sun, Rong Jin:
One Fits All: Universal Time Series Analysis by Pretrained LM and Specially Designed Adaptors. CoRR abs/2311.14782 (2023) - [i7]Yifan Zhang, Xue Wang, Tian Zhou, Kun Yuan, Zhang Zhang, Liang Wang, Rong Jin, Tieniu Tan:
Model-free Test Time Adaptation for Out-Of-Distribution Detection. CoRR abs/2311.16420 (2023) - [i6]Chao Chen, Tian Zhou, Yanjun Zhao, Hui Liu, Liang Sun, Rong Jin:
SVQ: Sparse Vector Quantization for Spatiotemporal Forecasting. CoRR abs/2312.03406 (2023) - 2022
- [c7]Chaoli Zhang, Tian Zhou, Qingsong Wen, Liang Sun:
TFAD: A Decomposition Time Series Anomaly Detection Architecture with Time-Frequency Analysis. CIKM 2022: 2497-2507 - [c6]Tian Zhou, Ziqing Ma, Qingsong Wen, Xue Wang, Liang Sun, Rong Jin:
FEDformer: Frequency Enhanced Decomposed Transformer for Long-term Series Forecasting. ICML 2022: 27268-27286 - [c5]Weiqi Chen, Wenwei Wang, Bingqing Peng, Qingsong Wen, Tian Zhou, Liang Sun:
Learning to Rotate: Quaternion Transformer for Complicated Periodical Time Series Forecasting. KDD 2022: 146-156 - [c4]Qingsong Wen, Linxiao Yang, Tian Zhou, Liang Sun:
Robust Time Series Analysis and Applications: An Industrial Perspective. KDD 2022: 4836-4837 - [c3]Tian Zhou, Ziqing Ma, Xue Wang, Qingsong Wen, Liang Sun, Tao Yao, Wotao Yin, Rong Jin:
FiLM: Frequency improved Legendre Memory Model for Long-term Time Series Forecasting. NeurIPS 2022 - [i5]Tian Zhou, Ziqing Ma, Qingsong Wen, Xue Wang, Liang Sun, Rong Jin:
FEDformer: Frequency Enhanced Decomposed Transformer for Long-term Series Forecasting. CoRR abs/2201.12740 (2022) - [i4]Qingsong Wen, Tian Zhou, Chaoli Zhang, Weiqi Chen, Ziqing Ma, Junchi Yan, Liang Sun:
Transformers in Time Series: A Survey. CoRR abs/2202.07125 (2022) - [i3]Tian Zhou, Ziqing Ma, Xue Wang, Qingsong Wen, Liang Sun, Tao Yao, Wotao Yin, Rong Jin:
FiLM: Frequency improved Legendre Memory Model for Long-term Time Series Forecasting. CoRR abs/2205.08897 (2022) - [i2]Tian Zhou, Jianqing Zhu, Xue Wang, Ziqing Ma, Qingsong Wen, Liang Sun, Rong Jin:
TreeDRNet: A Robust Deep Model for Long Term Time Series Forecasting. CoRR abs/2206.12106 (2022) - [i1]Chaoli Zhang, Tian Zhou, Qingsong Wen, Liang Sun:
TFAD: A Decomposition Time Series Anomaly Detection Architecture with Time-Frequency Analysis. CoRR abs/2210.09693 (2022)
2010 – 2019
- 2017
- [c2]Antong Chen, Tian Zhou, Ilknur Icke, Sarayu Parimal, Belma Dogdas, Joseph Forbes, Smita Sampath, Ansuman Bagchi, Chih-Liang Chin:
Transfer Learning for the Fully Automatic Segmentation of Left Ventricle Myocardium in Porcine Cardiac Cine MR Images. STACOM@MICCAI 2017: 21-31 - [c1]Tian Zhou, Ilknur Icke, Belma Dogdas, Sarayu Parimal, Smita Sampath, Joseph Forbes, Ansuman Bagchi, Chih-Liang Chin, Antong Chen:
Automatic segmentation of left ventricle in cardiac cine MRI images based on deep learning. Image Processing 2017: 101331W
Coauthor Index
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