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1908.05767
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Experimental performance of graph neural networks on random instances of max-cut
15 August 2019
Weichi Yao
Afonso S. Bandeira
Soledad Villar
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Papers citing
"Experimental performance of graph neural networks on random instances of max-cut"
19 / 19 papers shown
An Unsupervised Learning Framework Combined with Heuristics for the Maximum Minimal Cut Problem
Knowledge Discovery and Data Mining (KDD), 2024
Huaiyuan Liu
Xianzhang Liu
Donghua Yang
Hongzhi Wang
Yingchi Long
Mengtong Ji
Dongjing Miao
Zhiyu Liang
148
0
0
16 Aug 2024
A Benchmark for Maximum Cut: Towards Standardization of the Evaluation of Learned Heuristics for Combinatorial Optimization
Ankur Nath
Alan Kuhnle
CML
286
7
0
14 Jun 2024
A Unified Pre-training and Adaptation Framework for Combinatorial Optimization on Graphs
Science China Mathematics (Sci. China Math.), 2023
Ruibin Zeng
Minglong Lei
Lingfeng Niu
Lan Cheng
AI4CE
194
2
0
16 Dec 2023
Optimizing Solution-Samplers for Combinatorial Problems: The Landscape of Policy-Gradient Methods
Neural Information Processing Systems (NeurIPS), 2023
Constantine Caramanis
Eleni Psaroudaki
Alkis Kalavasis
Vasilis Kontonis
Christos Tzamos
338
5
0
08 Oct 2023
Controlling Continuous Relaxation for Combinatorial Optimization
Neural Information Processing Systems (NeurIPS), 2023
Yuma Ichikawa
468
16
0
29 Sep 2023
Monte Carlo Policy Gradient Method for Binary Optimization
Mathematical programming (Math. Program.), 2023
Cheng Chen
Ruitao Chen
Tian-cheng Li
Ruicheng Ao
Zaiwen Wen
136
6
0
03 Jul 2023
Towards fully covariant machine learning
Soledad Villar
D. Hogg
Weichi Yao
George A. Kevrekidis
Bernhard Schölkopf
AI4CE
356
13
0
31 Jan 2023
Unsupervised Learning for Combinatorial Optimization Needs Meta-Learning
International Conference on Learning Representations (ICLR), 2023
Hao Wang
Pan Li
252
23
0
08 Jan 2023
Learning Feasibility of Factored Nonlinear Programs in Robotic Manipulation Planning
IEEE International Conference on Robotics and Automation (ICRA), 2022
Joaquim Ortiz de Haro
Jung-Su Ha
Danny Driess
E. Karpas
Marc Toussaint
289
2
0
22 Oct 2022
Annealed Training for Combinatorial Optimization on Graphs
Haoran Sun
E. Guha
H. Dai
289
25
0
23 Jul 2022
Unsupervised Learning for Combinatorial Optimization with Principled Objective Relaxation
Neural Information Processing Systems (NeurIPS), 2022
Haoyu Wang
Nan Wu
Hang Yang
Cong Hao
Pan Li
459
43
0
13 Jul 2022
Graph neural network initialisation of quantum approximate optimisation
Quantum (Quantum), 2021
Nishant Jain
Brian Coyle
E. Kashefi
N. Kumar
GNN
AI4CE
432
59
0
04 Nov 2021
Combinatorial Optimization with Physics-Inspired Graph Neural Networks
M. Schuetz
J. K. Brubaker
H. Katzgraber
AI4CE
335
251
0
02 Jul 2021
Scalars are universal: Equivariant machine learning, structured like classical physics
Neural Information Processing Systems (NeurIPS), 2021
Soledad Villar
D. Hogg
Kate Storey-Fisher
Weichi Yao
Ben Blum-Smith
PINN
AI4CE
424
156
0
11 Jun 2021
Combinatorial optimization and reasoning with graph neural networks
International Joint Conference on Artificial Intelligence (IJCAI), 2021
Quentin Cappart
Didier Chételat
Elias Boutros Khalil
Andrea Lodi
Christopher Morris
Petar Velickovic
AI4CE
625
455
0
18 Feb 2021
The Power of Graph Convolutional Networks to Distinguish Random Graph Models: Short Version
International Symposium on Information Theory (ISIT), 2019
Abram Magner
Mayank Baranwal
Alfred Hero
GNN
173
14
0
13 Feb 2020
Can Graph Neural Networks Count Substructures?
Neural Information Processing Systems (NeurIPS), 2020
Zhengdao Chen
Lei Chen
Soledad Villar
Joan Bruna
GNN
693
363
0
10 Feb 2020
Fundamental Limits of Deep Graph Convolutional Networks
Abram Magner
Mayank Baranwal
Alfred Hero
GNN
262
7
0
28 Oct 2019
Graph Neural Networks for Maximum Constraint Satisfaction
Frontiers in Artificial Intelligence (FAI), 2019
Jan Toenshoff
Martin Ritzert
Hinrikus Wolf
Martin Grohe
GNN
NAI
AI4CE
310
69
0
18 Sep 2019
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