Transformers in time series: A survey Q Wen, T Zhou, C Zhang, W Chen, Z Ma, J Yan, L Sun arXiv preprint arXiv:2202.07125, 2022 | 487 | 2022 |
Multi-range attentive bicomponent graph convolutional network for traffic forecasting W Chen, L Chen, Y Xie, W Cao, Y Gao, X Feng Proceedings of the AAAI conference on artificial intelligence 34 (04), 3529-3536, 2020 | 281 | 2020 |
Learning to Rotate: Quaternion Transformer for Complicated Periodical Time Series Forecasting W Chen, W Wang, B Peng, Q Wen, T Zhou, L Sun 28th ACM SIGKDD Int. Conf. on Knowledge Discovery & Data Mining (KDD 2022), 2022 | 42 | 2022 |
AARGNN: An attentive attributed recurrent graph neural network for traffic flow prediction considering multiple dynamic factors L Chen, W Shao, M Lv, W Chen, Y Zhang, C Yang IEEE Transactions on Intelligent Transportation Systems 23 (10), 17201-17211, 2022 | 29 | 2022 |
Transformers in time series: A survey. arXiv Q Wen, T Zhou, C Zhang, W Chen, Z Ma, J Yan, L Sun arXiv preprint arXiv:2202.07125, 2022 | 23 | 2022 |
Dacha: A dual graph convolution based temporal knowledge graph representation learning method using historical relation L Chen, X Tang, W Chen, Y Qian, Y Li, Y Zhang ACM Transactions on Knowledge Discovery from Data (TKDD) 16 (3), 1-18, 2021 | 23 | 2021 |
Personalized federated darts for electricity load forecasting of individual buildings D Qin, C Wang, Q Wen, W Chen, L Sun, Y Wang IEEE Transactions on Smart Grid, 2023 | 10 | 2023 |
Learning from multiple time series: A deep disentangled approach to diversified time series forecasting L Chen, W Chen, B Wu, Y Zhang, B Wen, C Yang arXiv preprint arXiv:2111.04942, 2021 | 9 | 2021 |
Onenet: Enhancing time series forecasting models under concept drift by online ensembling Q Wen, W Chen, L Sun, Z Zhang, L Wang, R Jin, T Tan Advances in Neural Information Processing Systems 36, 2024 | 6 | 2024 |
Transformers in time series: a survey (2022) Q Wen, T Zhou, C Zhang, W Chen, Z Ma, J Yan, L Sun URL https://arxiv. org/abs/2202.07125, 0 | 6 | |
Energy forecasting with robust, flexible, and explainable machine learning algorithms Z Zhu, W Chen, R Xia, T Zhou, P Niu, B Peng, W Wang, H Liu, Z Ma, X Gu, ... AI Magazine 44 (4), 377-393, 2023 | 4 | 2023 |
eForecaster: unifying electricity forecasting with robust, flexible, and explainable machine learning algorithms Z Zhu, W Chen, R Xia, T Zhou, P Niu, B Peng, W Wang, H Liu, Z Ma, ... Proceedings of the AAAI Conference on Artificial Intelligence 37 (13), 15630 …, 2023 | 2 | 2023 |
Weathergnn: Exploiting complicated relationships in numerical weather prediction bias correction B Wu, W Chen, W Wang, B Peng, L Sun, L Chen arXiv preprint arXiv:2310.05517, 2023 | 1 | 2023 |
Time Series Subsequence Anomaly Detection via Graph Neural Networks W Chen, Z Zhou, Q Wen, L Sun | 1 | 2022 |
Learning to Extrapolate and Adjust: Two-Stage Meta-Learning for Concept Drift in Online Time Series Forecasting Z Zhu, W Chen, YF Zhang, Q Wen, L Sun | | 2023 |