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A Unified Pre-training and Adaptation Framework for Combinatorial
  Optimization on Graphs

A Unified Pre-training and Adaptation Framework for Combinatorial Optimization on Graphs

16 December 2023
Ruibin Zeng
Minglong Lei
Lingfeng Niu
Lan Cheng
    AI4CE
ArXiv (abs)PDFHTML

Papers citing "A Unified Pre-training and Adaptation Framework for Combinatorial Optimization on Graphs"

26 / 26 papers shown
Title
Structural Re-weighting Improves Graph Domain Adaptation
Structural Re-weighting Improves Graph Domain Adaptation
Shikun Liu
Tianchun Li
Yongbin Feng
Nhan Tran
Haiying Zhao
Qiu Qiang
Pan Li
OODAI4CE
59
39
0
05 Jun 2023
On Over-Squashing in Message Passing Neural Networks: The Impact of
  Width, Depth, and Topology
On Over-Squashing in Message Passing Neural Networks: The Impact of Width, Depth, and Topology
Francesco Di Giovanni
Lorenzo Giusti
Federico Barbero
Giulia Luise
Pietro Lio
Michael M. Bronstein
100
120
0
06 Feb 2023
Rethinking the Expressive Power of GNNs via Graph Biconnectivity
Rethinking the Expressive Power of GNNs via Graph Biconnectivity
Bohang Zhang
Shengjie Luo
Liwei Wang
Di He
48
123
0
23 Jan 2023
Revisiting Over-smoothing and Over-squashing Using Ollivier-Ricci
  Curvature
Revisiting Over-smoothing and Over-squashing Using Ollivier-Ricci Curvature
K. Nguyen
Hieu Nong
T. Nguyen
Nhat Ho
Khuong N. Nguyen
Vinh Phu Nguyen
75
68
0
28 Nov 2022
Evaluating Explainability for Graph Neural Networks
Evaluating Explainability for Graph Neural Networks
Chirag Agarwal
Owen Queen
Himabindu Lakkaraju
Marinka Zitnik
81
110
0
19 Aug 2022
Sym-NCO: Leveraging Symmetricity for Neural Combinatorial Optimization
Sym-NCO: Leveraging Symmetricity for Neural Combinatorial Optimization
Minsu Kim
Junyoung Park
Jinkyoo Park
121
88
0
26 May 2022
Self-Supervised Graph Neural Network for Multi-Source Domain Adaptation
Self-Supervised Graph Neural Network for Multi-Source Domain Adaptation
Jin Yuan
Feng Hou
Yangzhou Du
Zhongchao Shi
Xin Geng
Jianping Fan
Yong Rui
SSLOOD
59
20
0
08 Apr 2022
Neural Sheaf Diffusion: A Topological Perspective on Heterophily and
  Oversmoothing in GNNs
Neural Sheaf Diffusion: A Topological Perspective on Heterophily and Oversmoothing in GNNs
Cristian Bodnar
Francesco Di Giovanni
B. Chamberlain
Pietro Lio
Michael M. Bronstein
85
183
0
09 Feb 2022
Can Graph Neural Networks Learn to Solve MaxSAT Problem?
Can Graph Neural Networks Learn to Solve MaxSAT Problem?
Minghao Liu
Fuqi Jia
Pei Huang
Fan Zhang
Yuchen Sun
Shaowei Cai
Feifei Ma
Jian Zhang
GNNNAIAI4CE
106
8
0
15 Nov 2021
Combinatorial Optimization with Physics-Inspired Graph Neural Networks
Combinatorial Optimization with Physics-Inspired Graph Neural Networks
M. Schuetz
J. K. Brubaker
H. Katzgraber
AI4CE
83
185
0
02 Jul 2021
Learning to Optimize: A Primer and A Benchmark
Learning to Optimize: A Primer and A Benchmark
Tianlong Chen
Xiaohan Chen
Wuyang Chen
Howard Heaton
Jialin Liu
Zhangyang Wang
W. Yin
243
235
0
23 Mar 2021
Combinatorial optimization and reasoning with graph neural networks
Combinatorial optimization and reasoning with graph neural networks
Quentin Cappart
Didier Chételat
Elias Boutros Khalil
Andrea Lodi
Christopher Morris
Petar Velickovic
AI4CE
79
358
0
18 Feb 2021
Graph Neural Networks for Maximum Constraint Satisfaction
Graph Neural Networks for Maximum Constraint Satisfaction
Jan Toenshoff
Martin Ritzert
Hinrikus Wolf
Martin Grohe
GNNNAIAI4CE
54
60
0
18 Sep 2019
Graph Transfer Learning via Adversarial Domain Adaptation with Graph
  Convolution
Graph Transfer Learning via Adversarial Domain Adaptation with Graph Convolution
Quanyu Dai
Xiao-Ming Wu
Jiaren Xiao
Xiao Shen
Dan Wang
OOD
64
93
0
04 Sep 2019
Experimental performance of graph neural networks on random instances of
  max-cut
Experimental performance of graph neural networks on random instances of max-cut
Weichi Yao
Afonso S. Bandeira
Soledad Villar
72
38
0
15 Aug 2019
Exact Combinatorial Optimization with Graph Convolutional Neural
  Networks
Exact Combinatorial Optimization with Graph Convolutional Neural Networks
Maxime Gasse
Didier Chételat
Nicola Ferroni
Laurent Charlin
Andrea Lodi
GNNCML
142
488
0
04 Jun 2019
Graph Colouring Meets Deep Learning: Effective Graph Neural Network
  Models for Combinatorial Problems
Graph Colouring Meets Deep Learning: Effective Graph Neural Network Models for Combinatorial Problems
Henrique Lemos
Marcelo O. R. Prates
Pedro H. C. Avelar
Luís C. Lamb
GNN
54
85
0
11 Mar 2019
Combinatorial Optimization with Graph Convolutional Networks and Guided
  Tree Search
Combinatorial Optimization with Graph Convolutional Networks and Guided Tree Search
Zhuwen Li
Qifeng Chen
V. Koltun
GNN
94
475
0
25 Oct 2018
How Powerful are Graph Neural Networks?
How Powerful are Graph Neural Networks?
Keyulu Xu
Weihua Hu
J. Leskovec
Stefanie Jegelka
GNN
245
7,681
0
01 Oct 2018
Attention, Learn to Solve Routing Problems!
Attention, Learn to Solve Routing Problems!
W. Kool
H. V. Hoof
Max Welling
123
1,222
0
22 Mar 2018
Domain Adaptation on Graphs by Learning Aligned Graph Bases
Domain Adaptation on Graphs by Learning Aligned Graph Bases
Mehmet Pilanci
Elif Vural
OOD
44
52
0
14 Mar 2018
Graph Attention Networks
Graph Attention Networks
Petar Velickovic
Guillem Cucurull
Arantxa Casanova
Adriana Romero
Pietro Lio
Yoshua Bengio
GNN
479
20,225
0
30 Oct 2017
Inductive Representation Learning on Large Graphs
Inductive Representation Learning on Large Graphs
William L. Hamilton
Z. Ying
J. Leskovec
509
15,300
0
07 Jun 2017
Learning Combinatorial Optimization Algorithms over Graphs
Learning Combinatorial Optimization Algorithms over Graphs
H. Dai
Elias Boutros Khalil
Yuyu Zhang
B. Dilkina
Le Song
114
1,472
0
05 Apr 2017
Neural Message Passing for Quantum Chemistry
Neural Message Passing for Quantum Chemistry
Justin Gilmer
S. Schoenholz
Patrick F. Riley
Oriol Vinyals
George E. Dahl
596
7,485
0
04 Apr 2017
Semi-Supervised Classification with Graph Convolutional Networks
Semi-Supervised Classification with Graph Convolutional Networks
Thomas Kipf
Max Welling
GNNSSL
652
29,154
0
09 Sep 2016
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