《数学学迷信术申报(13)——Graph Convolutional Neural Networks: Deep Learning on Graphs and Beyond》-葡京app下载

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《数学学迷信术申报(13)——Graph Convolutional Neural Networks: Deep Learning on Graphs and Beyond》

来源:葡京app下载 作者:马国强 添加日期>2019-08-02 16:06:21 阅读次数:

申报题目: Graph Convolutional Neural Networks: Deep Learning on Graphs and Beyond
  申报人:李明 博士
  申报光阴>2019年08月02日(周一)15:00
  申报地点:格致中楼500集会室
  申报摘要:
  Learning and reasoning with graph-structured representations is gaining increasing interest in both academia and industry, due to its fundamental advantages over more traditional unstructured methods in supporting interpretability, causality, and transferability / inductive generalization. In this talk, I will briefly introduce the background about graph neural networks and some fundamentals around graph convolutional networks, for learning graph representations and performing reasoning and prediction. Some impressive progresses in this direction are provided with theoretical and empirical discussions.
  申报人简介:
  李明 博士, 澳大利亚 拉筹伯大学 数学与统计系博士后研究员、IEEE 会员、澳大利亚数学会会员、澳大利亚计算机协会会员。博士毕业于澳大利亚拉筹伯大学计算机迷信与信息技能专业,硕士研究生毕业于葡京app下载应用数学专业,本科毕业于山东师范大学信息与计算迷信专业。
  重要研究偏向为图神经收集,深度进修,神经收集随机进修算法,球面调和阐发,散乱数据插值与逼近。目前已在《IEEE Transactions on Cybernetics》、《Information Sciences》、《Computing》、《Applied Mathematics Modelling》、《Applied Mathematics and Computation》、《Mathematical Methods in the Applied Sciences》等刊物上发表学术论文多篇,曾获2016及2017年度国内期刊《IEEE Transactions on Cybernetics》最佳审稿人。
  迎接宽巨匠生加入!


理学院
2019年08月02日

 

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