tl;dr: We provably improve GNN expressivity by enhancing message passing with substructure encodings. Our method allows incorporating domain specific prior knowledge and can be used as a drop-in ...
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 ...
To effectively evaluate a system that performs operations on UML class diagrams, it is essential to cover a large variety of different types of diagrams. The coverage of the diagram space can be ...
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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