| Multivariate time-series anomaly detection via graph attention network H Zhao, Y Wang, J Duan, C Huang, D Cao, Y Tong, B Xu, J Bai, J Tong, ... 2020 IEEE international conference on data mining (ICDM), 841-850, 2020 | 670 | 2020 |
| Spectral temporal graph neural network for multivariate time-series forecasting D Cao, Y Wang, J Duan, C Zhang, X Zhu, C Huang, Y Tong, B Xu, J Bai, ... Advances in neural information processing systems 33, 17766-17778, 2020 | 636 | 2020 |
| TEMPO: Prompt-based generative pre-trained transformer for time series forecasting D Cao, F Jia, SO Arik, T Pfister, Y Zheng, W Ye, Y Liu ICLR 2024, 2023 | 170 | 2023 |
| When physics meets machine learning: A survey of physics-informed machine learning C Meng, S Seo, D Cao, S Griesemer, Y Liu arXiv preprint arXiv:2203.16797, 2022 | 97 | 2022 |
| Spectral temporal graph neural network for trajectory prediction D Cao, J Li, H Ma, M Tomizuka 2021 IEEE International Conference on Robotics and Automation (ICRA), 1839-1845, 2021 | 80 | 2021 |
| Gpt4mts: Prompt-based large language model for multimodal time-series forecasting F Jia, K Wang, Y Zheng, D Cao, Y Liu Proceedings of the AAAI Conference on Artificial Intelligence 38 (21), 23343 …, 2024 | 44 | 2024 |
| Counterfactual neural temporal point process for estimating causal influence of misinformation on social media Y Zhang, D Cao, Y Liu Advances in Neural Information Processing Systems (NeurIPS 2022), 2022 | 24 | 2022 |
| Detecting out-of-context multimodal misinformation with interpretable neural-symbolic model Y Zhang, L Trinh, D Cao, Z Cui, Y Liu arXiv preprint arXiv:2304.07633 2, 2023 | 20 | 2023 |
| Estimating Treatment Effects from Irregular Time Series Observations with Hidden Confounders D Cao, J Enouen, Y Wang, X Song, C Meng, H Niu, Y Liu AAAI 2023, 2023 | 20 | 2023 |
| FTCLNet: Convolutional LSTM with Fourier transform for vulnerability detection D Cao, J Huang, X Zhang, X Liu 2020 IEEE 19th International Conference on Trust, Security and Privacy in …, 2020 | 20 | 2020 |
| Mu2rest: Multi-resolution recursive spatio-temporal transformer for long-term prediction H Niu, C Meng, D Cao, G Habault, R Legaspi, S Wada, C Ono, Y Liu Pacific-Asia Conference on Knowledge Discovery and Data Mining, 68-80, 2022 | 12 | 2022 |
| Coupled multiwavelet neural operator learning for coupled partial differential equations X Xiao, D Cao, R Yang, G Gupta, G Liu, C Yin, R Balan, P Bogdan ICLR 2023, 2023 | 10 | 2023 |
| Neuro-inspired information-theoretic hierarchical perception for multimodal learning X Xiao, G Liu, G Gupta, D Cao, S Li, Y Li, T Fang, M Cheng, P Bogdan arXiv preprint arXiv:2404.09403, 2024 | 9 | 2024 |
| Svgformer: Representation learning for continuous vector graphics using transformers D Cao, Z Wang, J Echevarria, Y Liu Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2023 | 9 | 2023 |
| DSLOB: A Synthetic Limit Order Book Dataset for Benchmarking Forecasting Algorithms under Distributional Shift D Cao, Y El-Laham, L Trinh, S Vyetrenko, Y Liu NeurIPS 2022 on Distribution Shifts: Connecting Methods and Applications, 2022 | 9* | 2022 |
| Effects of Non‐Ionic Surfactants on the Rheological, Electrical and Electrochemical Properties of Highly Loaded Silicon Suspension Electrodes for Semi‐Solid Flow Batteries Y Wu, D Cao, X Bai, H Liu, H Hao, J Xing, J Dong, L Liao ChemElectroChem 7 (17), 3623-3631, 2020 | 9 | 2020 |
| Coupled Multiwavelet Operator Learning for Coupled Differential Equations X Xiao, D Cao, R Yang, G Gupta, G Liu, C Yin, R Balan, P Bogdan The 7th International Conference on Learning Representations, 0 | 9* | |
| Time-delayed multivariate time series predictions H Niu, G Habault, R Legaspi, C Meng, D Cao, S Wada, C Ono, Y Liu Proceedings of the 2023 SIAM International Conference on Data Mining (SDM …, 2023 | 8 | 2023 |
| Enhancing self-attention with knowledge-assisted attention maps J Bai, Y Wang, H Sun, R Wu, T Yang, P Tang, D Cao, M Zhang, Y Tong, ... Proceedings of the 2022 Conference of the North American Chapter of the …, 2022 | 8 | 2022 |
| An examination on the effectiveness of divide-and-conquer prompting in large language models Y Zhang, L Du, D Cao, Q Fu, Y Liu arXiv preprint arXiv:2402.05359, 2024 | 7 | 2024 |
Yan LiuProfessor, Director of Machine Learning Center@USCVerified email at usc.edu
