no code implementations • 3 Sep 2022 • Yingtao Luo, Chang Xu, Yang Liu, Weiqing Liu, Shun Zheng, Jiang Bian
In this work, we propose an learning framework that can automatically obtain interpretable PDE models from sequential data.
no code implementations • 4 Jul 2022 • Tianping Zhang, Yizhuo Zhang, Wei Cao, Jiang Bian, Xiaohan Yi, Shun Zheng, Jian Li
It uses less than 5% FLOPS compared with previous SOTA methods on the largest benchmark dataset.
1 code implementation • ICLR 2022 • Wei Fan, Shun Zheng, Xiaohan Yi, Wei Cao, Yanjie Fu, Jiang Bian, Tie-Yan Liu
However, the complicated dependencies of the PTS signal on its inherent periodicity as well as the sophisticated composition of various periods hinder the performance of PTS forecasting.
no code implementations • 9 Apr 2021 • Disheng Tang, Wei Cao, Jiang Bian, Tie-Yan Liu, Zhifeng Gao, Shun Zheng, Jue Liu
We used a stochastic metapopulation model with a hierarchical structure and fitted the model to the positive cases in the US from the start of outbreak to the end of 2020.
1 code implementation • 1 Jan 2021 • Yihan He, Wei Cao, Shun Zheng, Zhifeng Gao, Jiang Bian
In this work, we present a new method named Fourier Temporal State Embedding (FTSE) to address the temporal information in dynamic graph representation learning.
no code implementations • 1 Jan 2021 • Yihan He, Wei Cao, Shun Zheng, Zhifeng Gao, Jiang Bian
In recent years, research communities have been developing stochastic sampling methods to handle large graphs when it is unreal to put the whole graph into a single batch.
1 code implementation • ACL 2020 • Wentao Xu, Shun Zheng, Liang He, Bin Shao, Jian Yin, Tie-Yan Liu
In recent years, knowledge graph embedding becomes a pretty hot research topic of artificial intelligence and plays increasingly vital roles in various downstream applications, such as recommendation and question answering.
Ranked #1 on Link Prediction on YAGO37
2 code implementations • IJCNLP 2019 • Shun Zheng, Wei Cao, Wei Xu, Jiang Bian
Most existing event extraction (EE) methods merely extract event arguments within the sentence scope.
Ranked #4 on Document-level Event Extraction on ChFinAnn
1 code implementation • ACL 2019 • Shun Zheng, Xu Han, Yankai Lin, Peilin Yu, Lu Chen, Ling Huang, Zhiyuan Liu, Wei Xu
To demonstrate the effectiveness of DIAG-NRE, we apply it to two real-world datasets and present both significant and interpretable improvements over state-of-the-art methods.
no code implementations • 13 Apr 2016 • Shun Zheng, Jialei Wang, Fen Xia, Wei Xu, Tong Zhang
In modern large-scale machine learning applications, the training data are often partitioned and stored on multiple machines.