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Showing 1 to 4 of 4 for “"Subgraph classification"”.
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Subgraph classification through neighborhood pooling
Subgraph classification is an emerging field in graph representation learning where the task is to classify a group of nodes (i.e., a subgraph) within a graph. Graph neural networks (GNNs) are the de facto solution for node, link, and graph-level tasks but fail to perform well on subgraph …
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MPrompt: A Pretraining-Prompting Scheme for Enhanced Fewshot Subgraph Classification
… in node-level and graph-level learning tasks, subgraph-level tasks are highly underexplored, and the potential of prompting remains unclear. This thesis fills this gap by exploring the prompting mechanism for subgraph classification, which is a much more challenging task as it requires …
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Fast and Scalable Subgraph Learning
… do not support an emerging class of workloads: subgraph classification, which is increasingly common in real-world applications. Prior implementations address this gap by modifying both the data pipeline and the model architecture—but at the cost of composability, creating tightly coupled …
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Pretraining Table Embeddings for Knowledge Graph Based Provenance Systems
… this work examines the problem of provenance subgraph classification: given a coarser low-level provenance subgraph that is not easily digestible by humans, we want to annotate the subgraph with human readable labels describing the operations done on each data object. This work first involves …