Combinatorial Optimization with Physics-Inspired Graph Neural Networks

2 July 2021

Papers citing "Combinatorial Optimization with Physics-Inspired Graph Neural Networks"

50 / 65 papers shown

Title
Deep Symbolic Optimization: Reinforcement Learning for Symbolic Mathematics Conor F. Hayes Felipe Leno Da Silva Jiachen Yang T. Nathan Mundhenk Chak Shing Lee ... Ahmet Can Solak Thomas A. Desautels D. Faissol Brenden K. Petersen Mikel Landajuela 7 0 0 16 May 2025
A QUBO Framework for Team Formation Karan Vombatkere Evimaria Terzi Theodoros Lappas 41 0 0 29 Mar 2025
Riemannian Optimization on Relaxed Indicator Matrix Manifold Jinghui Yuan Fangyuan Xie Feiping Nie Xuelong Li 75 0 0 26 Mar 2025
Make Optimization Once and for All with Fine-grained Guidance Mingjia Shi Ruihan Lin Xuxi Chen Yuhao Zhou Zezhen Ding ... Tong Wang Kai Wang Zhangyang Wang Jingyang Zhang Tianlong Chen 55 1 0 14 Mar 2025
Preference-Based Gradient Estimation for ML-Based Approximate Combinatorial Optimization Arman Mielke Uwe Bauknecht Thilo Strauss Mathias Niepert 69 0 0 26 Feb 2025
Unrealized Expectations: Comparing AI Methods vs Classical Algorithms for Maximum Independent Set Yikai Wu Haoyu Zhao Sanjeev Arora 82 0 0 05 Feb 2025
Optimizing Job Allocation using Reinforcement Learning with Graph Neural Networks Lars C.P.M. Quaedvlieg 63 0 0 31 Jan 2025
Scalable Quantum-Inspired Optimization through Dynamic Qubit Compression Co Tran Quoc-Bao Tran Hy Truong Son Thang N Dinh 31 0 0 24 Dec 2024
Assessing and Enhancing Graph Neural Networks for Combinatorial Optimization: Novel Approaches and Application in Maximum Independent Set Problems Chenchuhui Hu 23 0 0 06 Nov 2024
A Unified Framework for Combinatorial Optimization Based on Graph Neural Networks Yaochu Jin Xueming Yan Shiqing Liu Xiangyu Wang 49 3 0 19 Jun 2024
A Benchmark for Maximum Cut: Towards Standardization of the Evaluation of Learned Heuristics for Combinatorial Optimization Ankur Nath Alan Kuhnle CML 49 3 0 14 Jun 2024
Decision-focused Graph Neural Networks for Combinatorial Optimization Yang Liu Chuan Zhou Peng Zhang Shirui Pan Zhao Li Hongyang Chen GNN AI4CE 41 1 0 05 Jun 2024
Combinatorial Optimization with Automated Graph Neural Networks Yang Liu Peng Zhang Yang Gao Chuan Zhou Zhao Li Hongyang Chen AI4CE GNN 33 2 0 05 Jun 2024
FlexiDrop: Theoretical Insights and Practical Advances in Random Dropout Method on GNNs Zhiheng Zhou Sihao Liu Weichen Zhao 24 0 0 30 May 2024
Learning Mixture-of-Experts for General-Purpose Black-Box Discrete Optimization Shengcai Liu Zhiyuan Wang Y. Ong Xin Yao Jiaheng Zhang OffRL 25 0 0 29 May 2024
Tackling Prevalent Conditions in Unsupervised Combinatorial Optimization: Cardinality, Minimum, Covering, and More Fanchen Bu Hyeonsoo Jo Soo Yong Lee Sungsoo Ahn Kijung Shin 22 3 0 14 May 2024
Hamiltonian-based Quantum Reinforcement Learning for Neural Combinatorial Optimization Georg Kruse Rodrigo Coehlo A. Rosskopf Robert Wille Jeanette Miriam Lorenz 30 1 0 13 May 2024
Dynamic Anisotropic Smoothing for Noisy Derivative-Free Optimization S. Reifenstein T. Leleu Yoshihisa Yamamoto 48 1 0 02 May 2024
Graph Coloring Using Heat Diffusion Vivek Chaudhary 21 0 0 21 Apr 2024
Message Passing Variational Autoregressive Network for Solving Intractable Ising Models Qunlong Ma Zhi Ma Jinlong Xu Hairui Zhang Ming Gao 27 5 0 09 Apr 2024
Graph Neural Aggregation-diffusion with Metastability Kaiyuan Cui Xinyan Wang Zicheng Zhang Weichen Zhao 39 2 0 29 Mar 2024
Towards Single-System Illusion in Software-Defined Vehicles -- Automated, AI-Powered Workflow Krzysztof Lebioda Viktor Vorobev Nenad Petrovic F. Pan Vahid Zolfaghari Alois C. Knoll 34 3 0 21 Mar 2024
A Short Review on Novel Approaches for Maximum Clique Problem: from Classical algorithms to Graph Neural Networks and Quantum algorithms Raffaele Marino L. Buffoni Bogdan Zavalnij GNN 40 5 0 13 Mar 2024
Efficient Combinatorial Optimization via Heat Diffusion He Ma Wenlian Lu Jianfeng Feng 34 1 0 13 Mar 2024
Artificial Intelligence for Complex Network: Potential, Methodology and Application Jingtao Ding Chang Liu Y. Zheng Yunke Zhang Zihan Yu ... Hongyi Chen J. Piao Huandong Wang Jiazhen Liu Yong Li AI4CE 29 10 0 23 Feb 2024
Graph Pruning for Enumeration of Minimal Unsatisfiable Subsets Panagiotis Lymperopoulos Liping Liu 38 0 0 19 Feb 2024
torchmSAT: A GPU-Accelerated Approximation To The Maximum Satisfiability Problem Abdelrahman I. Hosny Sherief Reda 13 1 0 06 Feb 2024
Continuous Tensor Relaxation for Finding Diverse Solutions in Combinatorial Optimization Problems Yuma Ichikawa Hiroaki Iwashita CLL 19 1 0 03 Feb 2024
Parametric Matrix Models Patrick Cook Danny Jammooa Morten Hjorth-Jensen Daniel D. Lee Dean Lee PINN 15 4 0 22 Jan 2024
A Unified Pre-training and Adaptation Framework for Combinatorial Optimization on Graphs Ruibin Zeng Minglong Lei Lingfeng Niu Lan Cheng AI4CE 19 0 0 16 Dec 2023
A Novel Differentiable Loss Function for Unsupervised Graph Neural Networks in Graph Partitioning Vivek Chaudhary 11 0 0 11 Dec 2023
A Graph Neural Network-Based QUBO-Formulated Hamiltonian-Inspired Loss Function for Combinatorial Optimization using Reinforcement Learning Redwan Ahmed Rizvee Raheeb Hassan Md. Mosaddek Khan 13 0 0 27 Nov 2023
Distributed Constrained Combinatorial Optimization leveraging Hypergraph Neural Networks Nasimeh Heydaribeni Xinrui Zhan Ruisi Zhang Tina Eliassi-Rad F. Koushanfar AI4CE 32 8 0 15 Nov 2023
Improved Sparse Ising Optimization K. Zick 27 2 0 15 Nov 2023
Benchmarking the optimization optical machines with the planted solutions N. Stroev N. Berloff Nir Davidson 27 0 0 12 Nov 2023
Maximum Independent Set: Self-Training through Dynamic Programming Lorenzo Brusca Lars C.P.M. Quaedvlieg Stratis Skoulakis Grigorios G. Chrysos V. Cevher SSL 19 7 0 28 Oct 2023
Optimizing Solution-Samplers for Combinatorial Problems: The Landscape of Policy-Gradient Methods C. Caramanis Dimitris Fotakis Alkis Kalavasis Vasilis Kontonis Christos Tzamos 11 5 0 08 Oct 2023
Are Graph Neural Networks Optimal Approximation Algorithms? Morris Yau Eric Lu Nikolaos Karalias Jessica Xu Stefanie Jegelka 26 1 0 01 Oct 2023
Controlling Continuous Relaxation for Combinatorial Optimization Yuma Ichikawa 32 4 0 29 Sep 2023
Monte Carlo Policy Gradient Method for Binary Optimization Cheng Chen Ruitao Chen Tian-cheng Li Ruicheng Ao Zaiwen Wen 15 3 0 03 Jul 2023
A Neural Separation Algorithm for the Rounded Capacity Inequalities Hyeon-Seob Kim Jinkyoo Park C. Kwon 44 6 0 29 Jun 2023
$Barriers for the performance of graph neural networks (GNN) in discrete random structures. A comment on~\cite{schuetz2022combinatorial},\cite{angelini2023modern},\cite{schuetz2023reply}$ Barriers for the performance of graph neural networks (GNN) in discrete random structures. A comment on~\cite{schuetz2022combinatorial},\cite{angelini2023modern},\cite{schuetz2023reply} D. Gamarnik 21 3 0 05 Jun 2023
Improving Expressivity of GNNs with Subgraph-specific Factor Embedded Normalization Kaixuan Chen Shunyu Liu Tongtian Zhu Tongya Zheng Haofei Zhang Zunlei Feng Jingwen Ye Mingli Song 42 14 0 31 May 2023
There is more to graphs than meets the eye: Learning universal features with self-supervision L. Das Sai Munikoti M. Halappanavar SSL OOD 27 1 0 31 May 2023
A Survey of Methods for Converting Unstructured Data to CSG Models Pierre-Alain Fayolle Markus Friedrich 3DPC 3DV 18 9 0 02 May 2023
Quantum approximate optimization via learning-based adaptive optimization Lixue Cheng Yu-Qin Chen Shi-Xin Zhang Shengyu Zhang 29 24 0 27 Mar 2023
Reply to: Inability of a graph neural network heuristic to outperform greedy algorithms in solving combinatorial optimization problems M. Schuetz J. K. Brubaker H. Katzgraber 33 2 0 03 Feb 2023
Reply to: Modern graph neural networks do worse than classical greedy algorithms in solving combinatorial optimization problems like maximum independent set M. Schuetz J. K. Brubaker H. Katzgraber 26 10 0 03 Feb 2023
A Graph Neural Network with Negative Message Passing for Graph Coloring Xiangyu Wang Xueming Yan Yaochu Jin 20 7 0 26 Jan 2023
Unsupervised Learning for Combinatorial Optimization Needs Meta-Learning Hao Wang Pan Li 13 14 0 08 Jan 2023