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We propose a universal Graph Neural Network architecture which can be trained as an end-2-end search heuristic for any Constraint Satisfaction Problem (CSP).
PDP: A general neural framework for learning constraint satisfaction solvers
Amizadeh, S.; Matusevych, S.; and Weimer, M. 2019 · 1903
Earlier work this paper cites.
A wide-ranging computational comparison of high-performance graph colouring algorithms
Lewis, R.; Thompson, J.; Mumford, C.; and Gillard, J. 2012 · 1950
Earlier work this paper cites.
New methods to color the vertices of a graph
Brélaz, D. 1979 · 1979
Earlier work this paper cites.
Simple statistical gradient-following algorithms for connectionist reinforcement learning
Williams, R. J. 1992 · 1992
Earlier work this paper cites.
Local search strategies for satisfiability testing
Selman, B.; Kautz, H. A.; Cohen, B.; et al. 1993 · 1993
Earlier work this paper cites.
Improved approximation algorithms for maximum cut and satisfiability problems using semidefinite programming
Goemans, M. X.; and Williamson, D. P. 1995 · 1995
Earlier work this paper cites.
Hybrid evolutionary algorithms for graph coloring
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Earlier work this paper cites.
Many Hard Examples in Exact Phase Transitions
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Earlier work this paper cites.
Learning TSP Requires Rethinking Generalization
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Earlier work this paper cites.
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Hagberg, A.; Swart, P.; and S Chult, D. 2008 · 2008
Earlier work this paper cites.
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Earlier work this paper cites.
A guide to graph colouring , volume 7
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Earlier work this paper cites.
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Earlier work this paper cites.
Pointer networks
Vinyals, O.; Fortunato, M.; and Jaitly, N. 2015 · 2015
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Gilmer, J.; Schoenholz, S. S.; Riley, P. F.; Vinyals, O.; and Dahl, G. E. 2017 · 2017
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Learning combinatorial optimization algorithms over graphs
Khalil, E.; Dai, H.; Zhang, Y.; Dilkina, B.; and Song, L. 2017 · 2017
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Veličković, P.; Cucurull, G.; Casanova, A.; Romero, A.; Lio, P.; and Bengio, Y. 2017 · 2017
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CoSoCo 1.12
Artificial Intelligence: A Modern Approach
Russell, S.; Russell, S.; Norvig, P.; and Davis, E. 2020 · 2020
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The Surprising Power of Graph Neural Networks with Random Node Initialization
Abboud, R.; Ceylan, İ. İ.; Grohe, M.; and Lukasiewicz, T. 2021 · 2021
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Handbook of Satisfiability
Biere, A.; Heule, M.; Van Maaren, H.; and Walsh, T. 2021 · 2021
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Combinatorial Optimization and Reasoning with Graph Neural Networks
Cappart, Q.; Chételat, D.; Khalil, E. B.; Lodi, A.; Morris, C.; and Veličković, P. 2021 · 2021
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Random features strengthen graph neural networks
Sato, R.; Yamada, M.; and Kashima, H. 2021 · 2021
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Graph Neural Networks for Maximum Constraint Satisfaction
Tönshoff, J.; Ritzert, M.; Wolf, H.; and Grohe, M. 2021 · 2021
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XCSP3 and its ecosystem
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Reversible Action Design for Combinatorial Optimization with Reinforcement Learning
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XCSP3 Competition 2022 Proceedings , XCSP3 Competition. Artois, France
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