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Deep Attributed Network Embedding by Preserving Structure and Attribute Information
Heterogeneous Network Embedding via Deep Architectures
Hierarchical Feature Embedding for Attribute Recognition
KDD tutorial part2 network embedding and GCN
How Neural Network Word Embeddings Actually Work
NSDI '17 - Correct by Construction Networks Using Stepwise Refinement
DeepWalk: Turning Graphs Into Features via Network Embeddings
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Last Updated: September 28, 2026
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Presented at the 16th International Workshop on Mining and Learning with Graphs (MLG), co-located with KDD 2020. Abstract ... BDCAT 2021 Paper Presentation Title: Author: Daixin Wang, Tsinghua University Abstract: For more information about Stanford's Artificial Intelligence professional and graduate programs, visit: stanford.io/3Cv1BEU ... Data Systems Seminar at Waterloo by Xiaokui Xiao on 14 June 2021. Authors: Zhijun Liu, Chao Huang, Yanwei Yu, Junyu Dong. Authors: Shiyu Chang, Wei Han, Jiliang Tang, Guo-Jun Qi, Charu C. Aggarwal, Thomas S. Huang Abstract: Data Authors: Jie Yang, Jiarou Fan, Yiru Wang, Yige Wang, Weihao Gan, Lin Liu, Wei Wu Description: KDD-2020-tutorial Recent Advances on Graph Analytics and Its Applications in Healthcare Part-2 ... Resources: This video is a part of my course: Modern AI: Applications and Overview ... Dr. Steven Skiena, Stony Brook University Michael Hunger, Neo4j Random walk algorithms help better model real-world ...
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