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 ...
If true, the following conjecture of Thomassen [Th81] is a planarity criterion for a special class of graphs that involves only K 5. Recall that a planar graph on n vertices contains at most 3n-6 ...
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 ...
Abstract: Many real-world relationships can be effectively represented as edge-labeled graphs, where edge labels encode semantic information vital for graph computations. Analyzing communities within ...
Graph cover problems form a critical area within discrete optimisation and theoretical computer science, addressing the challenge of selecting subsets of vertices (or edges) that satisfy predetermined ...
If you wish to reuse any or all of this article please use the link below which will take you to the Copyright Clearance Center’s RightsLink service. You will be ...
A breakthrough deal to attempt to limit global temperature rises was agreed at a conference of world nations in December 2015. These charts from the time show how and why the Earth’s climate is ...
diffusion/co_datasets, dataset wrappers. diffusion/models, neural networks. diffusion/tools, executable shell generation tools. diffusion/utils, task-specific utilities. diffusion/pl_meta_model.py, ...
This repository implements a semi-supervised learning approach for weed detection using YOLO and Graph Neural Networks. The system leverages both labeled and unlabeled data to improve detection ...
Dr. Gunjan Sharma develops DP-coloring frameworks to ensure seamless coordination and predictable complexity in large-scale ...
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