Nature

Graph Coloring Algorithms and Optimization Techniques

The graph colouring problem, a classic NP-hard challenge, is central to many practical applications such as scheduling, resource allocation and network management. Recent advances have seen the ...
Nature

Graph Curvature and Laplacian Operators

Graph curvature and Laplacian operators form a vibrant area of research at the intersection of differential geometry and graph theory. The concept of graph curvature, inspired by classical Ricci ...
IEEE

Combining Reinforcement Learning and Heuristic Optimization: A Model Based on a Deep Q-Network and Graph Neural Networks for Graph Coloring

Abstract: We present a hybrid approach combining Reinforcement Learning (RL) with the TabuCol, which is a version of tabu search specifically designed for the Graph Coloring Problem (GCP), enhanced by ...
GitHub

A game about graph theory and inductive logic.

For downloads, please see this game's itch.io page. For mathematical background and design notes, please see the author's page. This is a minimalist puzzle game that explores a variety of graph ...
IEEE

Semi-Supervised Learning With Graph Learning-Convolutional Networks

Abstract: Graph Convolutional Neural Networks (graph CNNs) have been widely used for graph data representation and semi-supervised learning tasks. However, existing graph CNNs generally use a fixed ...