文件名称：C:\Users\Wells\Desktop\[斯坦福大牛Jure Leskovec新课] CS224W：图机器学习 PPT.rar
文件大小：189.61MB
文件格式：RAR
更新时间：2023-01-20 04:37:28
图计算 机器学习 Jure Leskovec
2019 spring CS224W的PPT包+课程导读 Networks are a fundamental tool for modeling complex social, technological, and biological systems. Coupled with the emergence of online social networks and large-scale data availability in biological sciences, this course focuses on the analysis of massive networks which provide several computational, algorithmic, and modeling challenges. Students are introduced to machine learning techniques and data mining tools apt to reveal insights on the social, technological, and natural worlds, by means of studying their underlying network structure and interconnections. Topics include: robustness and fragility of food webs and financial markets; algorithms for the World Wide Web; graph neural networks and representation learning; identification of functional modules in biological networks; disease outbreak detection.
【文件预览】：
[斯坦福大牛Jure Leskovec新课] CS224W：图机器学习 PPT
----CS224W_Influence_Maximization_Handout.pdf(146KB)
----CS224W-snappy-tutorial.pdf(2.42MB)
----02-gnp-smallworld.pdf(5.5MB)
----09.txt(73B)
----导读.pdf(577KB)
----05-spectral.pdf(19.35MB)
----19-applications.pdf(37.47MB)
----07-noderepr.pdf(5.84MB)
----10-graph-gen.pdf(13MB)
----01-intro.pdf(24.81MB)
----08-GNN.pdf(24.88MB)
----06-collective.pdf(10.59MB)
----13-contagion.pdf(16.27MB)
----17-knowledge.pdf(9.42MB)
----11-pagerank.pdf(10.78MB)
----CS224W_LinAl_Prob_Proof.pdf(220KB)
----15-outbreak.pdf(4.26MB)
----03-motifs.pdf(14.23MB)
----12-cascades.pdf(9.95MB)
----18-limitations.pdf(7.4MB)
----04-communities.pdf(8.74MB)
----16-evolution.pdf(11.78MB)
----14-influence.pdf(6.55MB)