1 code implementation • 3 Nov 2023 • Mingze Yuan, Peng Bao, Jiajia Yuan, Yunhao Shen, ZiFan Chen, Yi Xie, Jie Zhao, Yang Chen, Li Zhang, Lin Shen, Bin Dong
This has sparked significant interest in applying LLMs to enhance various aspects of healthcare, ranging from medical education to clinical decision support.
1 code implementation • journal 2023 • Jianian Li, Peng Bao, Rong Yan, HuaWei Shen
In this paper, we propose a novel Dynamic graph representation framework via Tempo-Structural Contrastive Learning, DyTSCL, which trains the model by identifying three different subgraphs as a task, named Tempo-Structural subgraph, Non-Temporal subgraph and Non-Structural subgraph.
1 code implementation • journal 2023 • Rong Yan, Peng Bao
In the Curriculum Contrastive Training, we first utilize a triplet network to learn node representations by receiving original graph and different augmented views as input.
no code implementations • 20 Mar 2019 • Peng Bao, Wenjun Xia, Kang Yang, Weiyan Chen, Mianyi Chen, Yan Xi, Shanzhou Niu, Jiliu Zhou, He Zhang, Huaiqiang Sun, Zhangyang Wang, Yi Zhang
Over the past few years, dictionary learning (DL)-based methods have been successfully used in various image reconstruction problems.
no code implementations • 15 Oct 2018 • Peng Bao, Wenjun Xia, Kang Yang, Jiliu Zhou, Yi Zhang
Traditional dictionary learning based CT reconstruction methods are patch-based and the features learned with these methods often contain shifted versions of the same features.