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Shun Zheng
Shun Zheng
Microsoft Research Asia
Verified email at microsoft.com
Title
Cited by
Cited by
Year
Evaluation of individual and ensemble probabilistic forecasts of COVID-19 mortality in the United States
EY Cramer, EL Ray, VK Lopez, J Bracher, A Brennen, ...
Proceedings of the National Academy of Sciences 119 (15), e2113561119, 2022
313*2022
Doc2EDAG: An end-to-end document-level framework for Chinese financial event extraction
S Zheng, W Cao, W Xu, J Bian
EMNLP, 2019
2132019
Less is more: Fast multivariate time series forecasting with light sampling-oriented mlp structures
T Zhang, Y Zhang, W Cao, J Bian, X Yi, S Zheng, J Li
arXiv preprint arXiv:2207.01186, 2022
1462022
DEPTS: deep expansion learning for periodic time series forecasting
W Fan, S Zheng, X Yi, W Cao, Y Fu, J Bian, TY Liu
ICLR, 2022
592022
SEEK: Segmented embedding of knowledge graphs
W Xu, S Zheng, L He, B Shao, J Yin, TY Liu
ACL, 2020
362020
DIAG-NRE: A Neural Pattern Diagnosis Framework for Distantly Supervised Neural Relation Extraction
S Zheng, L Chen, L Huang, W Xu
ACL, 2019
352019
Efficient and effective multi-task grouping via meta learning on task combinations
X Song, S Zheng, W Cao, J Yu, J Bian
NeurIPS, 2022
342022
A general distributed dual coordinate optimization framework for regularized loss minimization
S Zheng, J Wang, F Xia, W Xu, T Zhang
Journal of Machine Learning Research 18 (115), 1-52, 2017
202017
From Supervised to Generative: A Novel Paradigm for Tabular Deep Learning with Large Language Models
X Wen, H Zhang, S Zheng, W Xu, J Bian
KDD, 2024
17*2024
Warpformer: A Multi-scale Modeling Approach for Irregular Clinical Time Series
J Zhang, S Zheng, W Cao, J Bian, J Li
KDD, 2023
172023
HierST: A unified hierarchical spatial-temporal framework for covid-19 trend forecasting
S Zheng, Z Gao, W Cao, J Bian, TY Liu
CIKM, 2021
142021
PTaRL: Prototype-based tabular representation learning via space calibration
H Ye, W Fan, X Song, S Zheng, H Zhao, D Guo, Y Chang
ICLR, 2024
122024
Learning differential operators for interpretable time series modeling
Y Luo, C Xu, Y Liu, W Liu, S Zheng, J Bian
KDD, 2022
102022
Revisiting the evaluation of end-to-end event extraction
S Zheng, W Cao, W Xu, J Bian
Findings of ACL, 2021
92021
Challenges of COVID-19 Case Forecasting in the US, 2020–2021
VK Lopez, EY Cramer, R Pagano, JM Drake, EB O’Dea, M Adee, T Ayer, ...
PLoS computational biology 20 (5), e1011200, 2024
72024
The CityLearn Challenge 2022: Overview, Results, and Lessons Learned
K Nweye, Z Nagy, S Mohanty, D Chakraborty, S Sankaranarayanan, ...
NeurIPS 2022 Competition Track, 85-103, 2022
72022
A continuous glucose monitoring measurements forecasting approach via sporadic blood glucose monitoring
Y Xing, H Ye, X Zhang, W Cao, S Zheng, J Bian, Y Guo
BIBM, 2022
62022
Addressing Distribution Shift in Time Series Forecasting with Instance Normalization Flows
W Fan, S Zheng, P Wang, R Xie, J Bian, Y Fu
arXiv preprint arXiv:2401.16777, 2024
52024
UADB: Unsupervised Anomaly Detection Booster
H Ye, Z Liu, X Shen, W Cao, S Zheng, X Gui, H Zhang, Y Chang, J Bian
ICDE, 2023
52023
Dewp: Deep expansion learning for wind power forecasting
W Fan, Y Fu, S Zheng, J Bian, Y Zhou, H Xiong
ACM Transactions on Knowledge Discovery from Data 18 (3), 1-21, 2024
32024
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