A Short Review on Novel Approaches for Maximum Clique Problem: from
Classical algorithms to Graph Neural Networks and Quantum algorithms

A Short Review on Novel Approaches for Maximum Clique Problem: from Classical algorithms to Graph Neural Networks and Quantum algorithms

13 March 2024

Raffaele Marino

Bogdan Zavalnij

ArXiv (abs)PDF HTML

Papers citing "A Short Review on Novel Approaches for Maximum Clique Problem: from Classical algorithms to Graph Neural Networks and Quantum algorithms"

17 / 17 papers shown

Title
Stochastic Gradient Descent-like relaxation is equivalent to Metropolis dynamics in discrete optimization and inference problems Maria Chiara Angelini A. Cavaliere Raffaele Marino F. Ricci-Tersenghi 104 5 0 11 Sep 2023
Reply to: Inability of a graph neural network heuristic to outperform greedy algorithms in solving combinatorial optimization problems M. Schuetz J. K. Brubaker H. Katzgraber 55 2 0 03 Feb 2023
Modern graph neural networks do worse than classical greedy algorithms in solving combinatorial optimization problems like maximum independent set Maria Chiara Angelini F. Ricci-Tersenghi GNN AI4CE 62 33 0 27 Jun 2022
Equivalence between algorithmic instability and transition to replica symmetry breaking in perceptron learning systems Yang Zhao Junbin Qiu Mingshan Xie Haiping Huang 10 4 0 26 Nov 2021
Learning the noise fingerprint of quantum devices Stefano Martina L. Buffoni S. Gherardini Filippo Caruso 26 26 0 23 Sep 2021
Combinatorial optimization and reasoning with graph neural networks Quentin Cappart Didier Chételat Elias Boutros Khalil Andrea Lodi Christopher Morris Petar Velickovic AI4CE 82 360 0 18 Feb 2021
Learning from Survey Propagation: a Neural Network for MAX-E- $3$ -SAT Raffaele Marino 59 14 0 10 Dec 2020
Solving non-linear Kolmogorov equations in large dimensions by using deep learning: a numerical comparison of discretization schemes Raffaele Marino N. Macris 55 16 0 09 Dec 2020
TUDataset: A collection of benchmark datasets for learning with graphs Christopher Morris Nils M. Kriege Franka Bause Kristian Kersting Petra Mutzel Marion Neumann 239 827 0 16 Jul 2020
A Survey on The Expressive Power of Graph Neural Networks Ryoma Sato 339 173 0 09 Mar 2020
Generalization and Representational Limits of Graph Neural Networks Vikas Garg Stefanie Jegelka Tommi Jaakkola GNN 101 314 0 14 Feb 2020
What graph neural networks cannot learn: depth vs width Andreas Loukas GNN 84 301 0 06 Jul 2019
Graph Neural Networks: A Review of Methods and Applications Jie Zhou Ganqu Cui Shengding Hu Zhengyan Zhang Cheng Yang Zhiyuan Liu Lifeng Wang Changcheng Li Maosong Sun AI4CE GNN 1.1K 5,532 0 20 Dec 2018
Machine Learning for Combinatorial Optimization: a Methodological Tour d'Horizon Yoshua Bengio Andrea Lodi Antoine Prouvost 155 1,392 0 15 Nov 2018
Geometric Scattering for Graph Data Analysis Feng Gao Guy Wolf M. Hirn GNN 68 113 0 07 Oct 2018
Finding Near-Optimal Independent Sets at Scale S. Lamm Peter Sanders Christian Schulz Darren Strash Renato F. Werneck 50 103 0 02 Sep 2015
The backtracking survey propagation algorithm for solving random K-SAT problems Raffaele Marino G. Parisi F. Ricci-Tersenghi 59 60 0 20 Aug 2015

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