Graph Information Bottleneck (GIB) for learning minimal sufficient structural and feature information using GNNs - snap-stanford/GIB
为此,我们提出了一个信息论指导原则,即鲁棒图信息瓶颈(Robust Graph Information Bottleneck,RGIB),以提取可靠的监督信号并避免表征坍缩。与基本的信息瓶颈GIB[4,5]不同的是,RGIB进一步解耦并平衡了图拓扑、图标签和图表征之间的相互依赖性,为抵抗双边噪声的鲁棒表征构建了新的学习目标。此外,我们探索了两种实例,R...
Structure-Aware Hierarchical Graph Pooling using Information Bottleneck, 📝IJCNN Mal2GCN: A Robust Malware Detection Approach Using Deep Graph Convolutional Networks With Non-Negative Weights, 📝arXiv CoG: a Two-View Co-training Framework for Defending Adversarial Attacks on Graph, 📝arXiv Releas...
The datasets supporting the conclusions of this article are publicly available, and the ‘Data and Hardware’ section lists all corresponding dataset identifiers and references. The C++ source code of Nexus is available at https://github.com/biointec/nexus under the GNU AGPL v3.0 license.Abbreviati...
html !pip install git+https://github.com/pyg-team/pytorch_geometric.git Powered By Planetoid Cora Dataset Planetoid is a citation network dataset from Cora, CiteSeer, and PubMed. The nodes are documents with 1433-dimensional bag-of-words feature vectors, and the edges are citation links ...
Our code is released at: https://github.com/lrjconan/GRAN.Renjie LiaoYujia LiYang SongShenlong WangWilliam L. HamiltonDavid DuvenaudRaquel UrtasunRichard ZemelAdvances in Neural Information Processing Systems 32, Volume 6 of 20: 32nd Conference on Neural Information Processing Systems (NeurIPS 2019)...
As part of our exhaustive analysis of existing contributions of different domains in the state-of-the-art of graph processing and storage, we provide direct links to source code repositories such as GitHub whenever they were available. Should the reader wish to delve into the implementation of a...
In this setting, nodes can directly communicate between each other even if they are not neighbors, breaking the information bottleneck and hence leading to more adequately learned representations. Our framework generalizes message passing neural networks, resulting in a class of more expressive models, ...
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