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, Yan Liu
   ICML 2024 Workshop | 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. Neuron-based Multifractal Analysis of Neuron Interaction Dynamics in Large Models
   Xiongye Xiao, Heng Ping, Chenyu Zhou, Defu Cao, Yaxing Li, Yizhuo Zhou, Shixuan Li, Nikos Kanakaris, Paul Bogdan
   ICLR 2025

2. When Splitting Makes Stronger: A Theoretical and Empirical Analysis of Divide-and-Conquer Prompting in LLMs
   Yizhou Zhang, Defu Cao, Lun Du, Qiang Fu, Yan Liu
   CoLM 2025

3. Active Sequential Posterior Estimation for Sample-Efficient Simulation-Based Inference
   Sam Griesemer, Defu Cao, Zijun Cui, Carolina Osorio, Yan Liu
   NeurIPS 2024

4. An Empirical Examination of Balancing Strategy for Counterfactual Estimation on Time Series
   Qiang Huang, Chuizheng Meng, Defu Cao, Biwei Huang, Yi Chang, Yan Liu
   ICML 2024

5. Neuro-Inspired Hierarchical Multimodal Learning
   Xiongye Xiao, Gengshuo Liu, Gaurav Gupta, Defu Cao, Shixuan Li, Yaxing Li, Tianqing Fang, Mingxi Cheng, Paul Bogdan
   ICLR 2024

6. MUGSI: Distilling GNNs with Multi-Granularity Structural Information for Graph Classification
   Tianjun Yao, Jiaqi Sun, Defu Cao, Kun Zhang, Guangyi Chen
   WWW 2024 | paper

7. Large Scale Financial Time Series Forecasting with Multi-Faceted Model
   Defu Cao, Yixiang Zheng, Parisa Hassanzadeh, Simran Lamba, Xiaomo Liu, Yan Liu
   ICAIF 2023 | Oral | paper

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

9. 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 2024 | paper

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

11. 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

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

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

14. 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

15. 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

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

17. 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%)

18. 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

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

Workshop Papers:

1. TimeDiT: General-purpose Diffusion Transformers for Time Series Foundation Model
   Defu Cao, Wen Ye, Yan Liu
   ICML 2024 Workshop on Foundation Models in the Wild | paper

2. 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 DistShift Workshop | paper | Proposed Dataset

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

Patents:

1. Representation Learning for Continuous Vector Graphics
   Defu Cao, Zhaowen Wang, Jose Echevarria US Patent Application US20240303870A1 | Status: Published Patent Application, United States, 2024 | USPTO

Publication Impact