Signal processing is crucial for satisfying the high data rate requirements of future sixth-generation (6G) wireless networks. However, the rapid growth of wireless networks has brought about massive ...

Analysis and processing of very large data sets, or big data, poses a significant challenge. Massive data sets are collected and studied in numerous domains, from engineering sciences to social ...

Advances in Chemical Representations and AI in Drug Discovery: The past century’s technological advancements, especially the computer revolution and high-throughput screening in drug discovery, have ...

In Graph RAG, entities and relationships are represented as nodes and edges in a knowledge graph. This structured representation can be mathematically modeled using graph theory concepts. Let G = (V, ...

Summary: Researchers discovered a unique feature of the human brain’s communication networks: the transmission of information via multiple parallel pathways, a trait not observed in macaques or mice.

This is the power of graph theory. However, graph theory doesn’t stop at social networks. It finds applications in everything from brain signal processing to solving Sudoku and airline scheduling.

SEAL_OGB -- An Implementation of SEAL for OGB Link Prediction Tasks About This repository supports the following paper: M. Zhang, P. Li, Y. Xia, K. Wang, and L. Jin, Labeling Trick: A Theory of Using ...

To get more insights into the involved research domains, Figure 3 shows a grouped list of search domains and their corresponding publication counts. The field of Information and Computing Sciences ...

The ability of graph neural networks (GNNs) to deal with graph data structures has made them suitable for real-life applications in social networks, bioinformatics, and navigation and planning ...