• # HIN2Vec

• Referenced in 6 articles [sw37750]
• them as features for multi-label node classification and link prediction applications on those networks ... micro$-$f_1\$ in multi-label node classification...
• # RolX

• Referenced in 8 articles [sw32343]
• making, searching for similar nodes, and node classification. This paper addresses the question: Given ... automatically discover roles for nodes? We propose RolX (Role eXtraction), a scalable (linear...
• # DropEdge

• Referenced in 3 articles [sw37753]
• Towards Deep Graph Convolutional Networks on Node Classification. Over-fitting and over-smoothing ... deep Graph Convolutional Networks (GCNs) for node classification. In particular, over-fitting weakens the generalization...
• # node2vec

• Referenced in 83 articles [sw27202]
• define a flexible notion of a node’s network neighborhood and design a biased random ... techniques on multi-label classification and link prediction in several real-world networks from diverse...
• # nodeHarvest

• Referenced in 2 articles [sw33154]
• nodeHarvest: Node Harvest for Regression and Classification. Node harvest is a simple interpretable tree-like ... high-dimensional regression and classification. A few nodes are selected from an initially large ensemble...
• # NetKit

• Referenced in 27 articles [sw22730]
• present NetKit, a modular toolkit for classification in net- worked data, and a case-study ... learning research. NetKit is based on a node-centric framework in which classifiers comprise...
• # CogDL

• Referenced in 2 articles [sw37740]
• tasks in the graph domain, including node classification, link prediction, graph classification, and other graph ... Most of the graph embedding methods learn node-level or graph-level representations...
• # HEPTHools

• Referenced in 3 articles [sw30615]
• each other via field redefinitions of the nodes. We extend this to non-valise adinkras ... Python code, providing a complete eigenvalue classification of “node-lifting” for all 36,864 valise...
• # struc2vec

• Referenced in 14 articles [sw36495]
• state-of-the-art techniques for learning node representations fail in capturing stronger notions ... experiments indicate that struc2vec improves performance on classification tasks that depend more on structural identity...
• # Sub2vec

• Referenced in 1 article [sw41562]
• learning algorithms for mining tasks like node classification and edge prediction. However, most ... work focuses on distributed representations of nodes that are inherently ill-suited to tasks such ... mining tasks, like community detection and graph classification. We show that Sub2Vec gets significant gains...
• # Devign

• Referenced in 3 articles [sw40145]
• neural network based model for graph-level classification through learning on a rich ... learned rich node representations for graph-level classification. The model is trained over manually labeled...
• # RANKS

• Referenced in 1 article [sw39968]
• RANKS: a flexible tool for node label ranking and classification in biological networks. Summary:RANKS ... bioinformatics task formalizable as ranking of nodes with respect to a property given...
• # Cheops

• Referenced in 1 article [sw29858]
• tend to break down. Hierarchies above 5000 nodes usually require special modifications such as clustering ... Decimal Classification system, which can contain between a million and a billion nodes. The Cheops ... deep classification hierarchy, which if fully populated would contain over 19 million nodes...