Graph-based semi-supervised learning for relational networks

15 December 2016

Papers citing "Graph-based semi-supervised learning for relational networks"

10 / 10 papers shown

Title
Simplifying Node Classification on Heterophilous Graphs with Compatible Label Propagation Zhiqiang Zhong Sergey Ivanov Jun Pang 61 9 0 19 May 2022
Large Scale Learning on Non-Homophilous Graphs: New Benchmarks and Strong Simple Methods Derek Lim Felix Hohne Xiuyu Li Sijia Huang Vaishnavi Gupta Omkar Bhalerao Ser-Nam Lim 149 361 0 27 Oct 2021
How does Heterophily Impact the Robustness of Graph Neural Networks? Theoretical Connections and Practical Implications Jiong Zhu Junchen Jin Donald Loveland Michael T. Schaub Danai Koutra AAML 108 37 0 14 Jun 2021
New Benchmarks for Learning on Non-Homophilous Graphs Derek Lim Xiuyu Li Felix Hohne Ser-Nam Lim 103 101 0 03 Apr 2021
Combining Label Propagation and Simple Models Out-performs Graph Neural Networks Qian Huang Horace He Abhay Singh Ser-Nam Lim Austin R. Benson 94 283 0 27 Oct 2020
Beyond Homophily in Graph Neural Networks: Current Limitations and Effective Designs Jiong Zhu Yujun Yan Lingxiao Zhao Mark Heimann Leman Akoglu Danai Koutra GNN 115 34 0 20 Jun 2020
Strongly local p-norm-cut algorithms for semi-supervised learning and local graph clustering Meng Liu D. Gleich 53 13 0 15 Jun 2020
Flow-based Algorithms for Improving Clusters: A Unifying Framework, Software, and Performance Kimon Fountoulakis M. Liu D. Gleich Michael W. Mahoney 76 11 0 20 Apr 2020
On Proximity and Structural Role-based Embeddings in Networks: Misconceptions, Techniques, and Applications Ryan A. Rossi Di Jin Sungchul Kim Nesreen Ahmed Danai Koutra J. B. Lee 70 38 0 22 Aug 2019
Community detection with spiking neural networks for neuromorphic hardware Kathleen E. Hamilton N. Imam Travis S. Humble 38 15 0 20 Nov 2017