Publications

Selected Topic: Time Series Foundation Model:

1. TEMPO: Prompt-based generative pre-trained transformer for time series forecasting
   Defu Cao, Furong Jia, Sercan O Arik, Tomas Pfister, Yixiang Zheng, Wen Ye, Yan Liu
   ICLR 2024 | paper | code | huggingface

2. TimeDiT: General-purpose Diffusion Transformers for Time Series Foundation Model
   Defu Cao, Wen Ye, Yizhou Zhang, Yan Liu
   Arxiv 2024 | paper

3. GPT4MTS: Prompt-based Large Language Model for Multimodal Time-series Forecasting
   Furong Jia, Kevin Wang, Yixiang Zheng, Defu Cao, Yan Liu
   AAAI/EAAI 2024 | paper | Multimodal Dataset

4. Beyond Forecasting: Compositional Time Series Reasoning for End-to-End Task Execution
   Wen Ye, Yizhou Zhang, Wei Yang, Lumingyuan Tang, Defu Cao, Jie Cai, Yan Liu
   Arxiv 2024 | paper

Survey Papers:

1. When Physics Meets Machine Learning: A Survey of Physics-Informed Machine Learning
   Chuizheng Meng, Sungyong Seo, Defu Cao, Sam Griesemer, Yan Liu
   Arxiv 2022 | paper

Conference Papers:

1. SVGformer: Representation Learning for Continuous Vector Graphics using Transformers
   Defu Cao, Zhaowen Wang, Jose Echevarria, Yan Liu
   CVPR 2023 | paper

2. Coupled Multiwavelet Neural Operator Learning for Coupled Partial Differential Equations
   Xiongye Xiao, Defu Cao, Ruochen Yang, Gaurav Gupta, Gengshuo Liu, Chenzhong Yin, Radu Balan, Paul Bogdan
   ICLR 2023 | paper

3. Time-delayed Multivariate Time Series Predictions
   Hao Niu, Guillaume Habault, Roberto Legaspi, Chuizheng Meng, Defu Cao, Shinya Wada, Chihiro Ono, Yan Liu
   SDM 2023

4. Estimating Treatment Effects from Irregular Time Series Observations with Hidden Confounders
   Defu Cao, James Enouen, Yujing Wang, Xiangchen Song, Chuizheng Meng, Hao Niu, Yan Liu
   AAAI 2023 | paper

5. Counterfactual Neural Temporal Point Process for Estimating Causal Influence of Misinformation on Social Media
   Yizhou Zhang, Defu Cao, Yan Liu
   NeurIPS 2022 | paper | code

6. Hardware Reusability Optimization for High-Level Synthesis of Component-Based Processors
   Xianhua Liu, Defu Cao, Qinshu Chen
   IEEE ICCCAS 2022 | paper

7. Enhancing Self-Attention with Knowledge-Assisted Attention Maps
   Jiangang Bai, Yujing Wang, Hong Sun, Ruonan Wu, Tianmeng Yang, Pengfei Tang, Wei Shen, Defu Cao, Mingliang Zhang, Yaming Yang, Jing Bai, Yunhai Tong, Hao Sun, Ruofei Zhang
   NAACL 2022 | paper

8. Mu2ReST: Multi-Resolution Recursive Spatio-Temporal Transformer for Long-Term Prediction
   Hao Niu, Chuizheng Meng, Defu Cao, Guillaume Habault, Roberto Legaspi, Shinya Wada, Chihiro Ono, Yan Liu
   PAKDD 2022 | paper

9. Spectral Temporal Graph Neural Network for Trajectory Prediction
   Defu Cao, Jiachen Li, Hengbo Ma, Masayoshi Tomizuka
   ICRA 2021 | paper

10. Spectral temporal graph neural network for multivariate time-series forecasting
    Defu Cao, Yujing Wang, Juanyong Duan, Ce Zhang, Xia Zhu, Conguri Huang, Yunhai Tong, Bixiong Xu, Jing Bai, Jie Tong, Qi Zhang
    NeurIPS 2020 | paper | code | video | Spotlight (2%)

11. Multivariate time-series anomaly detection via graph attention network
    Hang Zhao, Yujing Wang, Juanyong Duan, Congrui Huang, Defu Cao, Yunhai Tong, Bixiong Xu, Jing Bai, Jie Tong, Qi Zhang
    ICDM 2020 | paper | code

12. FTCLNet: Convolutional LSTM with Fourier Transform for Vulnerability Detection
    Defu Cao, Jing Huang, Xuanyu Zhang, Xianhua Liu
    TrustCom 2020 | paper

Workshop Papers:

1. DSLOB: A Synthetic Limit Order Book Dataset for Benchmarking Forecasting Algorithms under Distributional Shift
   Defu Cao, Yousef El-Laham, Loc Trinh, Svitlana Vyetrenko, Yan Liu
   NeurIPS 2022 | paper | Proposed Dataset

2. Estimating Treatment Effects in Continuous Time with Hidden Confounders
   Defu Cao, James Enouen, Yan Liu
   ICML 2022 | video | paper

Publication Impact