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Reply to: Modern graph neural networks do worse than classical greedy
  algorithms in solving combinatorial optimization problems like maximum
  independent set

Reply to: Modern graph neural networks do worse than classical greedy algorithms in solving combinatorial optimization problems like maximum independent set

Nature Machine Intelligence (Nat. Mach. Intell.), 2022
3 February 2023
M. Schuetz
J. K. Brubaker
H. Katzgraber
ArXiv (abs)PDFHTML

Papers citing "Reply to: Modern graph neural networks do worse than classical greedy algorithms in solving combinatorial optimization problems like maximum independent set"

3 / 3 papers shown
Title
Binarizing Physics-Inspired GNNs for Combinatorial Optimization
Binarizing Physics-Inspired GNNs for Combinatorial Optimization
Martin Krutsky
Gustav Sir
Vyacheslav Kungurtsev
Georgios Korpas
AI4CE
148
0
0
18 Jul 2025
Continuous Parallel Relaxation for Finding Diverse Solutions in Combinatorial Optimization Problems
Continuous Parallel Relaxation for Finding Diverse Solutions in Combinatorial Optimization Problems
Yuma Ichikawa
Hiroaki Iwashita
CLL
170
1
0
03 Feb 2024
A Graph Neural Network-Based QUBO-Formulated Hamiltonian-Inspired Loss
  Function for Combinatorial Optimization using Reinforcement Learning
A Graph Neural Network-Based QUBO-Formulated Hamiltonian-Inspired Loss Function for Combinatorial Optimization using Reinforcement Learning
Redwan Ahmed Rizvee
Raheeb Hassan
Md. Mosaddek Khan
113
1
0
27 Nov 2023
1