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DGGAT paper is indexed in IEEE

https://ieeexplore.ieee.org/abstract/document/10385796 Integrating Multi-omics Data into A Gated Graph Convolutional Networks for Identifying Cancer Driver Genes and Function Modules Publisher: IEEE Qianqian Peng; Zhihan He; Shichao Liu; Xinzhi Yao; Jingbo Xia Abstract: The identification of cancer driver genes is important for better understanding the hallmarks of cancer and developing precision therapies. Though the integration of multiomics and protein-protein interaction (PPI) dataContinueContinue reading “DGGAT paper is indexed in IEEE”

彭钱钱视频讲解DGGAT模型 ——《多组学和门控图卷积网络用于驱动基因和功能模块的预测》

❏ DGGAT模型 （多组学和门控图卷积网络用于驱动基因和功能模块的预测）时长: 10’01″/讲解: 英文/字幕：英文 https://youtu.be/R0HzJzFVxQ4 Youtube video DGGAT in BIBM, Istanbul, 2023(Algorithmic description of DGGAT model) B站镜像: Bilibili video Narrator: Qianqian Peng (彭钱钱)

彭钱钱做《针对图结构学习(GSL)问题中多截面图降噪的贝叶斯生成模型》报告

点击图片可观看该研究的汇报视频。如无跳转，可复制链接https://www.bilibili.com/video/BV1Ar4y1o7r6。 关键词：贝叶斯算法设计，图结构学习，证据上界，变分方法的神经网络实例化。 论文链接：https://link.springer.com/chapter/10.1007/978-3-031-40283-8_31