A Short Review on Novel Approaches for Maximum Clique Problem: from Classical algorithms to Graph Neural Networks and Quantum algorithms
<|reference_start|>A Short Review on Novel Approaches for Maximum Clique Problem: from Classical algorithms to Graph Neural Networks and Quantum algorithms: This manuscript provides a comprehensive review of the Maximum Clique Problem, a computational problem that involves finding subsets of vertices in a graph that are all pairwise adjacent to each other. The manuscript covers in a simple way classical algorithms for solving the problem and includes a review of recent developments in graph neural networks and quantum algorithms. The review concludes with benchmarks for testing classical as well as new learning, and quantum algorithms.<|reference_end|>
@article{marino2024a,
    title={A Short Review on Novel Approaches for Maximum Clique Problem: from
  Classical algorithms to Graph Neural Networks and Quantum algorithms},
    author={Raffaele Marino, Lorenzo Buffoni, Bogdan Zavalnij},
    journal={arXiv preprint arXiv:2403.09742},
    year={2024},
    archivePrefix={arXiv},
    eprint={2403.09742},
    primaryClass={cs.AI cond-mat.dis-nn cs.DS cs.LG math.OC quant-ph}
}