no code implementations • 22 Oct 2022 • ZHIXUN LI, Dingshuo Chen, Qiang Liu, Shu Wu
In this paper, we argue that the performance degradation is mainly attributed to the inconsistency between topology and attribute.
1 code implementation • 29 Sep 2022 • Yanqiao Zhu, Dingshuo Chen, Yuanqi Du, Yingze Wang, Qiang Liu, Shu Wu
Molecular pretraining, which learns molecular representations over massive unlabeled data, has become a prominent paradigm to solve a variety of tasks in computational chemistry and drug discovery.
1 code implementation • 8 Apr 2021 • Zekai Chen, Dingshuo Chen, Xiao Zhang, Zixuan Yuan, Xiuzhen Cheng
This paper presented GTA, a new framework for multivariate time series anomaly detection that involves automatically learning a graph structure, graph convolution, and modeling temporal dependency using a Transformer-based architecture.