ABSTRACT This work aims to study the equitable total coloring into subfamilies of regular graphs. For this purpose, we use some relationships between equitable total coloring and range (vertex) ...

Aggregate to Adapt: Node-Centric Aggregation for Multi-Source-Free Graph Domain Adaptation (WWW-2025). This is a PyTorch implementation of the GraphATA algorithm, which tries to address the ...

However, domain-specific approaches for extracting knowledge graph representations from semantic information remain limited. In this paper, we develop a natural language processing (NLP) approach to ...

The proposed method includes a multi-scale frequency domain feature extraction module, which uses 1-D channel convolutions of different scales to extract multi-scale frequency domain features.

The fast-rising pace of attacks is driving a graph database arms race across leading cybersecurity providers.

Large Language Models (LLMs) have revolutionized artificial intelligence applications across various fields, enabling domain experts to use pre-trained models for innovative solutions. While LLMs ...

Dynamic graphs arise in various real-world applications, and it is often welcomed to model the dynamics in continuous time domain for its flexibility. This paper aims to design an easy-to-use pipeline ...

Background and Purpose— Assessment of autoregulation in the time domain is a promising monitoring method for actively optimizating cerebral perfusion pressure (CPP) in critically ill patients. The ...

Collaborate to Adapt: Source-Free Graph Domain Adaptation via Bi-directional Adaptation (WWW 2024) This is a PyTorch implementation of the GraphCTA algorithm, which tries to address the domain ...