Graph technology is allowing pharma to model data in a way that offers invaluable insights for marketing, R&D and compliance teams alike. Google, Facebook and LinkedIn are among those utilising graph ...

Probabilistic graphs and uncertain data analysis represent a rapidly evolving research domain that seeks to reconcile the inherent imprecision of real-world data with robust computational models. By ...

Abstract: For many years, topological data analysis (TDA) and deep learning (DL) have been considered separate data analysis and representation learning approaches, which have nothing in common. The ...

Abstract: Variational Graph Autoencoders (VAGE) emerged as powerful graph representation learning methods with promising performance on graph analysis tasks. However, existing methods typically rely ...

The Stanford Web Graph represents the website structure of Stanford University, providing a detailed snapshot of how web pages within the Stanford domain are ...

Adam Hayes, Ph.D., CFA, is a financial writer with 15+ years Wall Street experience as a derivatives trader. Besides his extensive derivative trading expertise, Adam is an expert in economics and ...

This project provides a powerful and flexible PDF analysis microservice built with Clean Architecture principles. The service enables OCR, segmentation, and classification of different parts of PDF ...