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One Model, Any CSP: Graph Neural Networks as Fast Global Search
  Heuristics for Constraint Satisfaction

One Model, Any CSP: Graph Neural Networks as Fast Global Search Heuristics for Constraint Satisfaction

22 August 2022
Jan Tonshoff
Berke Kisin
Jakob Lindner
Martin Grohe
    GNN
ArXivPDFHTML

Papers citing "One Model, Any CSP: Graph Neural Networks as Fast Global Search Heuristics for Constraint Satisfaction"

13 / 13 papers shown
Title
Repetition Makes Perfect: Recurrent Sum-GNNs Match Message Passing Limit
Repetition Makes Perfect: Recurrent Sum-GNNs Match Message Passing Limit
Eran Rosenbluth
Martin Grohe
19
0
0
01 May 2025
Self-Supervised Transformers as Iterative Solution Improvers for Constraint Satisfaction
Self-Supervised Transformers as Iterative Solution Improvers for Constraint Satisfaction
Yudong Xu
Wenhao Li
Scott Sanner
Elias Boutros Khalil
39
0
0
18 Feb 2025
Beyond Interpolation: Extrapolative Reasoning with Reinforcement Learning and Graph Neural Networks
Beyond Interpolation: Extrapolative Reasoning with Reinforcement Learning and Graph Neural Networks
Niccolò Grillo
Andrea Toccaceli
Joël Mathys
Benjamin Estermann
Stefania Fresca
Roger Wattenhofer
AI4CE
LRM
99
0
0
06 Feb 2025
One Model, Any Conjunctive Query: Graph Neural Networks for Answering
  Complex Queries over Knowledge Graphs
One Model, Any Conjunctive Query: Graph Neural Networks for Answering Complex Queries over Knowledge Graphs
Krzysztof Olejniczak
Xingyue Huang
.Ismail .Ilkan Ceylan
Mikhail Galkin
GNN
49
0
0
21 Sep 2024
A Unified Framework for Combinatorial Optimization Based on Graph Neural
  Networks
A Unified Framework for Combinatorial Optimization Based on Graph Neural Networks
Yaochu Jin
Xueming Yan
Shiqing Liu
Xiangyu Wang
44
3
0
19 Jun 2024
A Benchmark for Maximum Cut: Towards Standardization of the Evaluation
  of Learned Heuristics for Combinatorial Optimization
A Benchmark for Maximum Cut: Towards Standardization of the Evaluation of Learned Heuristics for Combinatorial Optimization
Ankur Nath
Alan Kuhnle
CML
47
0
0
14 Jun 2024
A Diffusion Model Framework for Unsupervised Neural Combinatorial
  Optimization
A Diffusion Model Framework for Unsupervised Neural Combinatorial Optimization
Sebastian Sanokowski
Sepp Hochreiter
Sebastian Lehner
27
17
0
03 Jun 2024
Towards a Generic Representation of Combinatorial Problems for
  Learning-Based Approaches
Towards a Generic Representation of Combinatorial Problems for Learning-Based Approaches
Léo Boisvert
Hélene Verhaeghe
Quentin Cappart
14
5
0
09 Mar 2024
Are Graph Neural Networks Optimal Approximation Algorithms?
Are Graph Neural Networks Optimal Approximation Algorithms?
Morris Yau
Eric Lu
Nikolaos Karalias
Jessica Xu
Stefanie Jegelka
24
1
0
01 Oct 2023
Finding Hamiltonian cycles with graph neural networks
Finding Hamiltonian cycles with graph neural networks
Filip Bosnić
M. Šikić
9
1
0
10 Jun 2023
Some Might Say All You Need Is Sum
Some Might Say All You Need Is Sum
Eran Rosenbluth
Jan Toenshoff
Martin Grohe
15
16
0
22 Feb 2023
UNSAT Solver Synthesis via Monte Carlo Forest Search
UNSAT Solver Synthesis via Monte Carlo Forest Search
Chris Cameron
Jason S. Hartford
Taylor Lundy
T. Truong
Alan Milligan
Rex Chen
Kevin Leyton-Brown
21
1
0
22 Nov 2022
Graphically Structured Diffusion Models
Graphically Structured Diffusion Models
Christian Weilbach
William Harvey
Frank D. Wood
DiffM
27
7
0
20 Oct 2022
1