Graph databases are exploding, thanks to the AI boom - here's why

Data-hungry AI applications are fed complex information, and that's where graph databases and knowledge graphs play a crucial role.
IEEE

Graph Structure of Chebyshev Permutation Polynomials Over Ring ℤ p k

Abstract: Understanding the underlying graph structure of a nonlinear map over a particular domain is essential in evaluating its potential for real applications. In this paper, we investigate the ...
IEEE

Iterative polynomial approximation algorithms for inverse graph filters

Abstract: Chebyshev interpolation polynomials exhibit the exponential approximation property to analytic functions on a cube. Based on the Chebyshev interpolation polynomial approximation, we propose ...
lse

Graph Data Analytics and Representation Learning

This course is available on the MSc in Data Science, MSc in Geographic Data Science, MSc in Health Data Science, MSc in Operations Research & Analytics, MSc in Quantitative Methods for Risk Management ...
Investopedia

Strip Bonds Explained: Definition, Function, Returns, and Examples

What Is a Strip Bond? A strip bond detaches the principal and regular coupon payments, selling them separately as new securities. Known also as zero-coupon bonds, these investments, free from ...
GitHub

Struct2GO:protein function prediction based on Graph pooling algorithm and AlphaFold2 structure information

Struct2GO is a protein function prediction model based on self-attention graph pooling, which utilizes structural information from AlphaFold2 to augment the accuracy and generality of the model's ...
GitHub

ProtHGT: Heterogeneous Graph Transformers for Automated Protein Function Prediction Using Knowledge Graphs and Language Models

The rapid accumulation of protein sequence data, coupled with the slow pace of experimental annotations, creates a critical need for computational methods to predict protein functions. Existing models ...