Transfer Learning for the Fully Automatic Segmentation of Left Ventricle Myocardium in Porcine Cardiac Cine MR Images. - Antong Chen; Tian Zhou 004; Ilknur Icke; Sarayu Parimal; Belma Dogdas; Joseph Forbes; Smita Sampath; Ansuman Bagchi; Chih-Liang Chin (STACOM@MICCAI, 2017)

Automatic segmentation of left ventricle in cardiac cine MRI images based on deep learning. - Tian Zhou 004; Ilknur Icke; Belma Dogdas; Sarayu Parimal; Smita Sampath; Joseph Forbes; Ansuman Bagchi; Chih-Liang Chin; Antong Chen (Image Processing, 2017)

TFAD: A Decomposition Time Series Anomaly Detection Architecture with Time-Frequency Analysis. - Chaoli Zhang 001; Tian Zhou 004; Qingsong Wen; Liang Sun 001 (CIKM, 2022)

FEDformer: Frequency Enhanced Decomposed Transformer for Long-term Series Forecasting. - Tian Zhou 004; Ziqing Ma; Qingsong Wen; Xue Wang 010; Liang Sun 001; Rong Jin 001 (ICML, 2022)

Learning to Rotate: Quaternion Transformer for Complicated Periodical Time Series Forecasting. - Weiqi Chen; Wenwei Wang; Bingqing Peng; Qingsong Wen; Tian Zhou 004; Liang Sun 001 (KDD, 2022)

Robust Time Series Analysis and Applications: An Industrial Perspective. - Qingsong Wen; Linxiao Yang; Tian Zhou 004; Liang Sun 001 (KDD, 2022)

FiLM: Frequency improved Legendre Memory Model for Long-term Time Series Forecasting. - Tian Zhou 004; Ziqing Ma; Xue Wang 010; Qingsong Wen; Liang Sun 001; Tao Yao; Wotao Yin; Rong Jin 001 (NeurIPS, 2022)

TreeDRNet: A Robust Deep Model for Long Term Time Series Forecasting. - Tian Zhou 004; Jianqing Zhu; Xue Wang 010; Ziqing Ma; Qingsong Wen; Liang Sun 001; Rong Jin 001 (CoRR, 2022)

eForecaster: Unifying Electricity Forecasting with Robust, Flexible, and Explainable Machine Learning Algorithms. - Zhaoyang Zhu; Weiqi Chen; Rui Xia; Tian Zhou 004; Peisong Niu; Bingqing Peng; Wenwei Wang; Hengbo Liu; Ziqing Ma; Qingsong Wen; Liang Sun 001 (AAAI, 2023)

GCformer: An Efficient Solution for Accurate and Scalable Long-Term Multivariate Time Series Forecasting. - Yanjun Zhao; Ziqing Ma; Tian Zhou 004; Mengni Ye; Liang Sun 001; Yi Qian 004 (CIKM, 2023)

SADI: A Self-Adaptive Decomposed Interpretable Framework for Electric Load Forecasting Under Extreme Events. - Hengbo Liu; Ziqing Ma; Linxiao Yang; Tian Zhou 004; Rui Xia; Yi Wang 022; Qingsong Wen; Liang Sun 001 (ICASSP, 2023)

Transformers in Time Series: A Survey. - Qingsong Wen; Tian Zhou 004; Chaoli Zhang 001; Weiqi Chen; Ziqing Ma; Junchi Yan; Liang Sun 001 (IJCAI, 2023)

DCdetector: Dual Attention Contrastive Representation Learning for Time Series Anomaly Detection. - Yiyuan Yang; Chaoli Zhang 001; Tian Zhou 004; Qingsong Wen; Liang Sun 001 (KDD, 2023)

One Fits All: Power General Time Series Analysis by Pretrained LM. - Tian Zhou 004; Peisong Niu; Xue Wang 010; Liang Sun 001; Rong Jin 001 (NeurIPS, 2023)

Power Time Series Forecasting by Pretrained LM. - Tian Zhou 004; Peisong Niu; Xue Wang 010; Liang Sun 001; Rong Jin 001 (CoRR, 2023)

How Expressive are Spectral-Temporal Graph Neural Networks for Time Series Forecasting? - Ming Jin 005; Guangsi Shi; Yuan-Fang Li; Qingsong Wen; Bo Xiong; Tian Zhou 004; Shirui Pan (CoRR, 2023)

Make Transformer Great Again for Time Series Forecasting: Channel Aligned Robust Dual Transformer. - Xue Wang 010; Tian Zhou 004; Qingsong Wen; Jinyang Gao; Bolin Ding; Rong Jin 001 (CoRR, 2023)

GCformer: An Efficient Framework for Accurate and Scalable Long-Term Multivariate Time Series Forecasting. - Yanjun Zhao; Ziqing Ma; Tian Zhou 004; Liang Sun 001; Mengni Ye; Yi Qian 004 (CoRR, 2023)

One Fits All: Universal Time Series Analysis by Pretrained LM and Specially Designed Adaptors. - Tian Zhou 004; Peisong Niu; Xue Wang 010; Liang Sun 001; Rong Jin 001 (CoRR, 2023)

Model-free Test Time Adaptation for Out-Of-Distribution Detection. - Yifan Zhang 004; Xue Wang 010; Tian Zhou 004; Kun Yuan 001; Zhang Zhang 001; Liang Wang 001; Rong Jin 001; Tieniu Tan (CoRR, 2023)

SVQ: Sparse Vector Quantization for Spatiotemporal Forecasting. - Chao Chen; Tian Zhou 004; Yanjun Zhao; Hui Liu 023; Liang Sun 001; Rong Jin 001 (CoRR, 2023)

Energy forecasting with robust, flexible, and explainable machine learning algorithms. - Zhaoyang Zhu; Weiqi Chen; Rui Xia; Tian Zhou 004; Peisong Niu; Bingqing Peng; Wenwei Wang; Hengbo Liu; Ziqing Ma; Xinyue Gu; Jin Wang; Qiming Chen; et al. (AI Mag., 2023)

CARD: Channel Aligned Robust Blend Transformer for Time Series Forecasting. - Xue Wang 010; Tian Zhou 004; Qingsong Wen; Jinyang Gao; Bolin Ding; Rong Jin 001 (ICLR, 2024)

FusionSF: Fuse Heterogeneous Modalities in a Vector Quantized Framework for Robust Solar Power Forecasting. - Ziqing Ma; Wenwei Wang; Tian Zhou 004; Chao Chen; Bingqing Peng; Liang Sun 001; Rong Jin 001 (KDD, 2024)

Attention as Robust Representation for Time Series Forecasting. - Peisong Niu; Tian Zhou 004; Xue Wang 010; Liang Sun 001; Rong Jin 001 (CoRR, 2024)

Sparse-VQ Transformer: An FFN-Free Framework with Vector Quantization for Enhanced Time Series Forecasting. - Yanjun Zhao; Tian Zhou 004; Chao Chen; Liang Sun 001; Yi Qian 004; Rong Jin 001 (CoRR, 2024)

S3Attention: Improving Long Sequence Attention with Smoothed Skeleton Sketching. - Xue Wang 010; Tian Zhou 004; Jianqing Zhu; Jialin Liu 003; Kun Yuan 001; Tao Yao; Wotao Yin; Rong Jin 001; HanQin Cai (CoRR, 2024)

Mitigating Time Discretization Challenges with WeatherODE: A Sandwich Physics-Driven Neural ODE for Weather Forecasting. - Peiyuan Liu; Tian Zhou 004; Liang Sun 001; Rong Jin 001 (CoRR, 2024)

S$^ text{3}$Attention: Improving Long Sequence Attention With Smoothed Skeleton Sketching. - Xue Wang 010; Tian Zhou 004; Jianqing Zhu; Jialin Liu 003; Kun Yuan 001; Tao Yao; Wotao Yin; Rong Jin 001; HanQin Cai (IEEE J. Sel. Top. Signal Process., 2024)

Unlocking the Power of LSTM for Long Term Time Series Forecasting. - Yaxuan Kong; Zepu Wang; Yuqi Nie; Tian Zhou 004; Stefan Zohren; Yuxuan Liang; Peng Sun; Qingsong Wen (AAAI, 2025)

Less Is More: Embracing Sparsity and Interpolation with Esiformer for Time Series Forecasting. - Yangyang Guo; Yanjun Zhao; Sizhe Dang; Tian Zhou 004; Liang Sun 001; Yi Qian 004 (ICASSP, 2025)

Sparse-VQ Transformer: An FFN-Free Framework with Vector Quantization for Enhanced Time Series. - Yanjun Zhao; Tian Zhou 004; Chao Chen; Liang Sun 001; Yi Qian 004; Rong Jin 001 (ICASSP, 2025)

Utilizing Strategic Pre-training to Reduce Overfitting: Baguan - A Pre-trained Weather Forecasting Model. - Peisong Niu; Ziqing Ma; Tian Zhou 004; Weiqi Chen; Lefei Shen; Rong Jin 001; Liang Sun 001 (CoRR, 2025)

Output Scaling: YingLong-Delayed Chain of Thought in a Large Pretrained Time Series Forecasting Model. - Xue Wang 010; Tian Zhou 004; Jinyang Gao; Bolin Ding; Jingren Zhou 001 (CoRR, 2025)

Towards Expressive Spectral-Temporal Graph Neural Networks for Time Series Forecasting. - Ming Jin 005; Guangsi Shi; Yuan-Fang Li; Bo Xiong; Tian Zhou 004; Flora D. Salim; Liang Zhao 002; Lingfei Wu 001; Qingsong Wen; Shirui Pan (IEEE Trans. Pattern Anal. Mach. Intell., 2025)