Node classification is one of the core tasks on attributed graphs, but successful graph learning solutions require sufficiently labeled data. To keep annotation costs low, active graph learning focuses on selecting the most qualitative subset of nodes that maximizes label efficiency. However, deciding ...
Official repository for NeurIPS 2023 paper "When Do Graph Neural Networks Help with Node Classification? Investigating the Impact of Homophily Principle on Node Distinguishability" Resources Readme License MIT license Activity Stars 19 stars Watchers 4 watching Forks 4 forks Report repository ...
Kipf, Thomas N., and Max Welling. “Semi-Supervised Classification with Graph Convolutional Networks.” Paper presented at ICLR 2017, Toulon, France, April 2017. Blum, Lorenz C., and Jean-Louis Reymond. “970 Million Druglike Small Molecules for Virtual Screening in the Chemical Universe Databa...
Code for NeurIPS 2021 paper "Topology-Imbalance Learning for Semi-Supervised Node Classification" This work investigates thetopology-imbalanceproblem of node representation learning on graph-structured data. Unlike the "quantity-imbalance" problem, the topology imbalance is caused by the topological properti...
This paper focuses on capturing rich semantics within heterogeneous graphs for node representation learning and node classification. We present an algorithm to extract multi-level semantics on heterogeneous graphs. For node semantics, our algorithm can capture node-to-node interactions through double-node...
Each node is associated with a d-dimension signal/feature vector, so the signals of graph GG form a matrix X∈RN×d=[xT1;…;xTN]X∈RN×d=[x1T;…;xNT] where xixi is the signal vector of the i-th node. For the semi-supervised node classification, the expected output is a label...
Node-Graph MVGRL Graph & Node classification Node-Node GRACE Node classification Node-Node GCA Node classification Node-Node BGRL Node classification Node-Node GBT Node classification 不同的对比模式介绍完了,下面介绍一下aligned views和non-aligned views(这一概念主要针对node-node contrasting mode)。align...
To this end, using the genetic algorithm (GA) as a framework, in this paper we propose a GNN search method (called GCN-GA) that dynamically searches the depth of the model to efficiently handle the node classification tasks. First, a variable-length encoding strategy is proposed to use the...
However, most existent node predictors fail to capture a wide range of node patterns or to make predictions based on distinct node patterns, resulting in unsatisfactory classification performance. In this paper, we reveal that different node predictors are good at handling nodes with specific patterns...
Node Classification on PPI Leaderboard Dataset View by F1GraphSAGEGraphSAGEGATGATGaANGaANCluster-GCNCluster-GCNGraphStarGraphStarGraphSAINTGraphSAINTGCNII*GCNII*g2-MLPg2-MLPOther modelsModels with highest F1Jul '17Jan '18Jul '18Jan '19Jul '19Jan '20Jul '20Jan '21...