This repository supports the following paper: M. Zhang, P. Li, Y. Xia, K. Wang, and L. Jin, Labeling Trick: A Theory of Using Graph Neural Networks for Multi-Node Representation Learning. [PDF] SEAL ...
In this tutorial, we implement Tree-KG, an advanced hierarchical knowledge graph system that goes beyond traditional retrieval-augmented generation by combining semantic embeddings with explicit graph ...
We aim to build a pre-trained Graph Neural Network (GNN) model on molecules without human annotations or prior knowledge. Although various attempts have been proposed to overcome limitations in ...
The microbiome represents a complex community of trillions of microorganisms residing in various body parts and plays critical roles in maintaining host health and wellbeing. Understanding the ...
Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. The processing of chemical information by computational intelligence methods faces the ...
Abstract: The rise of graph analytic systems has created a need for ways to measure and compare the capabilities of these systems. Graph analytics present unique scalability difficulties. The machine ...
Abstract: Conventional intent-driven networks (IDNs) rely on static templates to translate declarative intents into imperative network configurations. However, the dynamic nature of network ...
This article introduces a model-based design, implementation, deployment, and execution methodology, with tools supporting the systematic composition of algorithms from generic and domain-specific ...
Article subjects are automatically applied from the ACS Subject Taxonomy and describe the scientific concepts and themes of the article. The “SmartGraph network-pharmacology investigation platform” (1 ...
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