Qingsong Wen (文青松)
Qingsong Wen (文青松)
Head of AI Research & Chief Scientist @ Squirrel AI
Verified email at - Homepage
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FEDformer: Frequency enhanced decomposed transformer for long-term series forecasting
T Zhou, Z Ma, Q Wen, X Wang, L Sun, R Jin
The 39th Int. Conf. on Machine Learning (ICML 2022), 2022
Time Series Data Augmentation for Deep Learning: A Survey
Q Wen, L Sun, F Yang, X Song, J Gao, X Wang, H Xu
The 30th Int. Joint Conf. on Artificial Intelligence (IJCAI 2021), 2021
Transformers in Time Series: A Survey
Q Wen, T Zhou, C Zhang, W Chen, Z Ma, J Yan, L Sun
The 32nd Int. Joint Conf. on Artificial Intelligence (IJCAI 2023), 2023
RobustSTL: A Robust Seasonal-Trend Decomposition Algorithm for Long Time Series
Q Wen, J Gao, X Song, L Sun, H Xu, S Zhu
The 33rd AAAI Conference on Artificial Intelligence (AAAI 2019) 33 (01 …, 2019
RobustTAD: Robust Time Series Anomaly Detection via Decomposition and Convolutional Neural Networks
J Gao, X Song, Q Wen, P Wang, L Sun, H Xu
ACM SIGKDD 2020 Workshop on Mining and Learning from Time Series (KDD 2020 WS), 2020
A class of low complexity PTS techniques for PAPR reduction in OFDM systems
Y Xiao, X Lei, Q Wen, S Li
IEEE Signal Processing Letters (SPL 2007) 14 (10), 680-683, 2007
Time-LLM: Time Series Forecasting by Reprogramming Large Language Models
M Jin, S Wang, L Ma, Z Chu, JY Zhang, X Shi, PY Chen, Y Liang, YF Li, ...
International Conference on Learning Representations (ICLR 2024), 2024
FiLM: Frequency improved Legendre Memory Model for Long-term Time Series Forecasting
T Zhou, Z Ma, X Wang, Q Wen, L Sun, T Yao, W Yin, R Jin
36th Conf. on Neural Information Processing Systems (NeurIPS 2022 Oral), 2022
Fast RobustSTL: Efficient and Robust Seasonal-Trend Decomposition for Time Series with Complex Patterns
Q Wen, Z Zhang, Y Li, L Sun
ACM SIGKDD Conf. on Knowledge Discovery & Data Mining (KDD 2020), 2020
A survey on graph neural networks for time series: Forecasting, classification, imputation, and anomaly detection
M Jin, HY Koh, Q Wen, D Zambon, C Alippi, GI Webb, I King, S Pan
arXiv preprint arXiv:2307.03759, 2023
RobustPeriod: Robust Time-Frequency Mining for Multiple Periodicity Detection
Q Wen, K He, L Sun, Y Zhang, M Ke, H Xu
ACM 2021 Int. Conf. on Management of Data (SIGMOD 2021), 2328-2337, 2021
AirFormer: Predicting Nationwide Air Quality in China with Transformers
Y Liang, Y Xia, S Ke, Y Wang, Q Wen, J Zhang, Y Zheng, R Zimmermann
The 37th AAAI Conference on Artificial Intelligence (AAAI 2023), 2023
Self-Supervised Learning for Time Series Analysis: Taxonomy, Progress, and Prospects
K Zhang, Q Wen, C Zhang, R Cai, M Jin, Y Liu, J Zhang, Y Liang, G Pang, ...
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024, 2024
TFAD: A Decomposition Time Series Anomaly Detection Architecture with Time-Frequency Analysis
C Zhang, T Zhou, Q Wen, L Sun
31st ACM Int. Conf. on Information & Knowledge Management (CIKM 2022), 2497-2507, 2022
Nonlinearity reduction by tone reservation with null subcarriers for WiMAX system
S Hu, G Wu, Q Wen, Y Xiao, S Li
Wireless Personal Communications (WPC 2010) 54, 289-305, 2010
Large models for time series and spatio-temporal data: A survey and outlook
M Jin, Q Wen, Y Liang, C Zhang, S Xue, X Wang, J Zhang, Y Wang, ...
arXiv preprint arXiv:2310.10196, 2023
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
CloudRCA: A Root Cause Analysis Framework for Cloud Computing Platforms
Y Zhang, Z Guan, H Qian, L Xu, H Liu, Q Wen, L Sun, J Jiang, L Fan, M Ke
ACM International Conference on Information and Knowledge Management (CIKM 2021), 2021
DCdetector: Dual Attention Contrastive Representation Learning for Time Series Anomaly Detection
Y Yang, C Zhang, T Zhou, Q Wen, L Sun
29th ACM SIGKDD Int. Conf. on Knowledge Discovery & Data Mining (KDD 2023), 2023
Robust Time Series Analysis and Applications: An Industrial Perspective
Q Wen, L Yang, T Zhou, L Sun
28th ACM SIGKDD Int. Conf. on Knowledge Discovery & Data Mining (KDD 2022), 2022
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