ResearchTrend.AI
  • Papers
  • Communities
  • Events
  • Blog
  • Pricing
Papers
Communities
Social Events
Terms and Conditions
Pricing
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2025 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 2505.19497
  4. Cited By
Learning for Dynamic Combinatorial Optimization without Training Data

Learning for Dynamic Combinatorial Optimization without Training Data

26 May 2025
Yiqiao Liao
Farinaz Koushanfar
Parinaz Naghizadeh
    GNN
    AI4CE
ArXivPDFHTML

Papers citing "Learning for Dynamic Combinatorial Optimization without Training Data"

27 / 27 papers shown
Title
Fast T2T: Optimization Consistency Speeds Up Diffusion-Based Training-to-Testing Solving for Combinatorial Optimization
Fast T2T: Optimization Consistency Speeds Up Diffusion-Based Training-to-Testing Solving for Combinatorial Optimization
Yang Li
Jinpei Guo
Runzhong Wang
H. Zha
Junchi Yan
111
10
0
05 Feb 2025
Fast, Scalable, Warm-Start Semidefinite Programming with Spectral
  Bundling and Sketching
Fast, Scalable, Warm-Start Semidefinite Programming with Spectral Bundling and Sketching
Rico Angell
Andrew McCallum
61
2
0
19 Dec 2023
Variational Annealing on Graphs for Combinatorial Optimization
Variational Annealing on Graphs for Combinatorial Optimization
Sebastian Sanokowski
Wilhelm Berghammer
Sepp Hochreiter
Sebastian Lehner
72
15
0
23 Nov 2023
Distributed Constrained Combinatorial Optimization leveraging Hypergraph
  Neural Networks
Distributed Constrained Combinatorial Optimization leveraging Hypergraph Neural Networks
Nasimeh Heydaribeni
Xinrui Zhan
Ruisi Zhang
Tina Eliassi-Rad
F. Koushanfar
AI4CE
59
10
0
15 Nov 2023
Controlling Continuous Relaxation for Combinatorial Optimization
Controlling Continuous Relaxation for Combinatorial Optimization
Yuma Ichikawa
65
6
0
29 Sep 2023
DIFUSCO: Graph-based Diffusion Solvers for Combinatorial Optimization
DIFUSCO: Graph-based Diffusion Solvers for Combinatorial Optimization
Zhiqing Sun
Yiming Yang
DiffM
57
125
0
16 Feb 2023
Unsupervised Learning for Combinatorial Optimization Needs Meta-Learning
Unsupervised Learning for Combinatorial Optimization Needs Meta-Learning
Hao Wang
Pan Li
28
15
0
08 Jan 2023
DIMES: A Differentiable Meta Solver for Combinatorial Optimization
  Problems
DIMES: A Differentiable Meta Solver for Combinatorial Optimization Problems
Ruizhong Qiu
Zhiqing Sun
Yiming Yang
90
83
0
08 Oct 2022
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
Jan Tönshoff
Berke Kisin
Jakob Lindner
Martin Grohe
GNN
48
24
0
22 Aug 2022
Graph Neural Network Guided Local Search for the Traveling Salesperson
  Problem
Graph Neural Network Guided Local Search for the Traveling Salesperson Problem
Benjamin H. Hudson
Qingbiao Li
Matthew Malencia
Amanda Prorok
46
65
0
11 Oct 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
51
183
0
02 Jul 2021
Learning the Travelling Salesperson Problem Requires Rethinking
  Generalization
Learning the Travelling Salesperson Problem Requires Rethinking Generalization
Chaitanya K. Joshi
Quentin Cappart
Louis-Martin Rousseau
T. Laurent
110
114
0
12 Jun 2020
PyTorch: An Imperative Style, High-Performance Deep Learning Library
PyTorch: An Imperative Style, High-Performance Deep Learning Library
Adam Paszke
Sam Gross
Francisco Massa
Adam Lerer
James Bradbury
...
Sasank Chilamkurthy
Benoit Steiner
Lu Fang
Junjie Bai
Soumith Chintala
ODL
274
42,038
0
03 Dec 2019
Graph Neural Networks for Maximum Constraint Satisfaction
Graph Neural Networks for Maximum Constraint Satisfaction
Jan Toenshoff
Martin Ritzert
Hinrikus Wolf
Martin Grohe
GNN
NAI
AI4CE
36
59
0
18 Sep 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
GNN
CML
110
481
0
04 Jun 2019
An Efficient Graph Convolutional Network Technique for the Travelling
  Salesman Problem
An Efficient Graph Convolutional Network Technique for the Travelling Salesman Problem
Chaitanya K. Joshi
T. Laurent
Xavier Bresson
GNN
81
364
0
04 Jun 2019
Fast Graph Representation Learning with PyTorch Geometric
Fast Graph Representation Learning with PyTorch Geometric
Matthias Fey
J. E. Lenssen
3DH
GNN
3DPC
169
4,303
0
06 Mar 2019
Attention, Learn to Solve Routing Problems!
Attention, Learn to Solve Routing Problems!
W. Kool
H. V. Hoof
Max Welling
83
1,193
0
22 Mar 2018
Graph Attention Networks
Graph Attention Networks
Petar Velickovic
Guillem Cucurull
Arantxa Casanova
Adriana Romero
Pietro Lio
Yoshua Bengio
GNN
319
19,991
0
30 Oct 2017
Inductive Representation Learning on Large Graphs
Inductive Representation Learning on Large Graphs
William L. Hamilton
Z. Ying
J. Leskovec
403
15,066
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
90
1,453
0
05 Apr 2017
Neural Combinatorial Optimization with Reinforcement Learning
Neural Combinatorial Optimization with Reinforcement Learning
Irwan Bello
Hieu H. Pham
Quoc V. Le
Mohammad Norouzi
Samy Bengio
123
1,472
0
29 Nov 2016
Semi-Supervised Classification with Graph Convolutional Networks
Semi-Supervised Classification with Graph Convolutional Networks
Thomas Kipf
Max Welling
GNN
SSL
447
28,901
0
09 Sep 2016
Convolutional Neural Networks on Graphs with Fast Localized Spectral
  Filtering
Convolutional Neural Networks on Graphs with Fast Localized Spectral Filtering
M. Defferrard
Xavier Bresson
P. Vandergheynst
GNN
253
7,622
0
30 Jun 2016
Pointer Networks
Pointer Networks
Oriol Vinyals
Meire Fortunato
Navdeep Jaitly
96
3,036
0
09 Jun 2015
Delving Deep into Rectifiers: Surpassing Human-Level Performance on
  ImageNet Classification
Delving Deep into Rectifiers: Surpassing Human-Level Performance on ImageNet Classification
Kaiming He
Xinming Zhang
Shaoqing Ren
Jian Sun
VLM
200
18,534
0
06 Feb 2015
What's in a crowd? Analysis of face-to-face behavioral networks
What's in a crowd? Analysis of face-to-face behavioral networks
L. Isella
J. Stehlé
Alain Barrat
C. Cattuto
J. Pinton
W. V. D. Broeck
65
811
0
07 Jun 2010
1