Learning from the Dark: Boosting Graph Convolutional Neural Networks with Diverse Negative Samples

3 October 2022

Papers citing "Learning from the Dark: Boosting Graph Convolutional Neural Networks with Diverse Negative Samples"

8 / 8 papers shown

Title
RW-NSGCN: A Robust Approach to Structural Attacks via Negative Sampling Shuqi He Jun Zhuang Ding Wang Jun Song AAML 37 0 0 13 Aug 2024
Heterophilous Distribution Propagation for Graph Neural Networks Zhuonan Zheng Sheng Zhou Hongjia Xu Ming Gu Yilun Xu Ao Li Yuhong Li Jingjun Gu Jiajun Bu 58 0 0 31 May 2024
Group-Aware Coordination Graph for Multi-Agent Reinforcement Learning Wei Duan Jie Lu Junyu Xuan 40 6 0 17 Apr 2024
Inferring Latent Temporal Sparse Coordination Graph for Multi-Agent Reinforcement Learning Wei Duan Jie Lu Junyu Xuan 40 3 0 28 Mar 2024
Layer-diverse Negative Sampling for Graph Neural Networks Wei Duan Jie Lu Yu Guang Wang Junyu Xuan 34 4 0 18 Mar 2024
Balancing Augmentation with Edge-Utility Filter for Signed GNNs Ke-Jia Chen Yaming Ji Youran Qu Chuhan Xu 34 0 0 25 Oct 2023
Graph Convolutional Neural Networks with Diverse Negative Samples via Decomposed Determinant Point Processes Wei Duan Junyu Xuan Maoying Qiao Jie Lu 31 8 0 05 Dec 2022
Determinantal point processes for machine learning Alex Kulesza B. Taskar 176 1,124 0 25 Jul 2012