A gentle introduction to Graph Neural Networks in Pytorch Geometric. Teaching material for machine learning on graphs' lectures and lab. sessions held for the i) Social Network Analysis course, Master ...

The core of this patent lies in its ability to generate multimodal hybrid interview questions. The system dynamically generates personalized interview questions based on candidates' resumes and ...

These utility functions are ideal for demonstration as they comprise a number of different graph-based subproblems, and thus demonstrate the usefulness of our method over a wide range.

Home | Mathematics | Linear functions, graphs and equations | Graphing linear functions Graphing linear functions This section focuses on the key features and methods for working with linear graphs.

Introduction Paternal prepubertal passive smoke exposure may increase the risk of childhood asthma. However, its association ...

Graph neural networks have a variety of applications in different fields of science where graph theory has its application. One of such fields is indoor localization and mapping problems. One of ...

PGQL, a new SQL standard, simplifies querying connected data in relational tables. Oracle 23ai supports PGQL, enabling efficient graph traversal and analysis, offering easier data discovery and deeper ...

Introduction We propose a graph context-conditioned diffusion model called InstructG2I to generate images from multimodal attributed graphs (MMAGs). InstructG2I first exploits the graph structure and ...

From calculators to ChatGPT, the introduction of new technology into schools has long inspired frenzied discourse: Will it revolutionize the system or rot kids’ brains? It often does neither.

Recently, a research team from the Hong Kong University of Science and Technology (Guangzhou) and Tencent published findings ...

Supply is a fundamental economic concept that describes the total amount of a specific good or service that's offered to ...