{"total":98,"rows":[{"id":"2102.09544","title":"Combinatorial optimization and reasoning with graph neural networks","created":"2021-02-18","cited_by_count":268,"area":null},{"id":"2210.04123","title":"DIMES: A Differentiable Meta Solver for Combinatorial Optimization Problems","created":"2022-10-08","cited_by_count":129,"area":null},{"id":"2106.06610","title":"Scalars are universal: Equivariant machine learning, structured like classical physics","created":"2021-06-11","cited_by_count":127,"area":null},{"id":"2107.01188","title":"Combinatorial Optimization with Physics-Inspired Graph Neural Networks","created":"2021-07-02","cited_by_count":108,"area":null},{"id":"2106.11113","title":"Matrix Encoding Networks for Neural Combinatorial Optimization","created":"2021-06-21","cited_by_count":91,"area":null},{"id":"2203.15386","title":"Pareto Set Learning for Neural Multi-objective Combinatorial Optimization","created":"2022-03-29","cited_by_count":56,"area":null},{"id":"2507.16991","title":"PyG 2.0: Scalable Learning on Real World Graphs","created":"2025-07-22","cited_by_count":52,"area":null},{"id":"2205.14210","title":"MIP-GNN: A Data-Driven Framework for Guiding Combinatorial Solvers","created":"2022-05-27","cited_by_count":49,"area":null},{"id":"2203.08509","title":"Differentiable DAG Sampling","created":"2022-03-16","cited_by_count":47,"area":null},{"id":"2305.17010","title":"Let the Flows Tell: Solving Graph Combinatorial Optimization Problems with GFlowNets","created":"2023-05-26","cited_by_count":40,"area":null},{"id":"2207.05984","title":"Unsupervised Learning for Combinatorial Optimization with Principled Objective Relaxation","created":"2022-07-13","cited_by_count":32,"area":null},{"id":"2211.00692","title":"Towards Better Out-of-Distribution Generalization of Neural Algorithmic Reasoning Tasks","created":"2022-11-01","cited_by_count":30,"area":null},{"id":"2202.01606","title":"Graph Coloring with Physics-Inspired Graph Neural Networks","created":"2022-02-03","cited_by_count":29,"area":null},{"id":"2106.04927","title":"A Bi-Level Framework for Learning to Solve Combinatorial Optimization on Graphs","created":"2021-06-09","cited_by_count":26,"area":null},{"id":"2206.01506","title":"Can Hybrid Geometric Scattering Networks Help Solve the Maximum Clique Problem?","created":"2022-06-03","cited_by_count":25,"area":null},{"id":"2202.08396","title":"Augment with Care: Contrastive Learning for Combinatorial Problems","created":"2022-02-17","cited_by_count":22,"area":null},{"id":"2311.14156","title":"Variational Annealing on Graphs for Combinatorial Optimization","created":"2023-11-23","cited_by_count":21,"area":null},{"id":"2301.03116","title":"Unsupervised Learning for Combinatorial Optimization Needs Meta-Learning","created":"2023-01-08","cited_by_count":20,"area":null},{"id":"2206.13181","title":"Learning to Control Local Search for Combinatorial Optimization","created":"2022-06-27","cited_by_count":18,"area":null},{"id":"2207.11542","title":"Annealed Training for Combinatorial Optimization on Graphs","created":"2022-07-23","cited_by_count":18,"area":null},{"id":"2309.16965","title":"Controlling Continuous Relaxation for Combinatorial Optimization","created":"2023-09-29","cited_by_count":16,"area":null},{"id":"2407.13917","title":"LinSATNet: The Positive Linear Satisfiability Neural Networks","created":"2024-07-18","cited_by_count":16,"area":null},{"id":"2208.04055","title":"Neural Set Function Extensions: Learning with Discrete Functions in High Dimensions","created":"2022-08-08","cited_by_count":14,"area":null},{"id":"2107.01410","title":"Maximum Entropy Weighted Independent Set Pooling for Graph Neural Networks","created":"2021-07-03","cited_by_count":12,"area":null},{"id":"2310.00526","title":"Are Graph Neural Networks Optimal Approximation Algorithms?","created":"2023-10-01","cited_by_count":11,"area":null},{"id":"2503.19173","title":"Graph neural networks extrapolate out-of-distribution for shortest paths","created":"2025-03-24","cited_by_count":11,"area":null},{"id":"2107.01952","title":"Partition and Code: learning how to compress graphs","created":"2021-07-05","cited_by_count":10,"area":null},{"id":"2502.00277","title":"Regularized Langevin Dynamics for Combinatorial Optimization","created":"2025-02-01","cited_by_count":10,"area":null},{"id":"2402.10977","title":"Generative AI and Process Systems Engineering: The Next Frontier","created":"2024-02-15","cited_by_count":9,"area":null},{"id":"2505.24067","title":"Primal-Dual Neural Algorithmic Reasoning","created":"2025-05-29","cited_by_count":9,"area":null},{"id":"2104.03546","title":"Graph Partitioning and Sparse Matrix Ordering using Reinforcement Learning and Graph Neural Networks","created":"2021-04-08","cited_by_count":8,"area":null},{"id":"2108.04623","title":"Maximizing Influence with Graph Neural Networks","created":"2021-08-10","cited_by_count":8,"area":null},{"id":"2210.11020","title":"Maximum Common Subgraph Guided Graph Retrieval: Late and Early Interaction Networks","created":"2022-10-20","cited_by_count":8,"area":null},{"id":"2111.10285","title":"Adversarial Deep Learning for Online Resource Allocation","created":"2021-11-19","cited_by_count":7,"area":null},{"id":"2405.08424","title":"Tackling Prevalent Conditions in Unsupervised Combinatorial Optimization: Cardinality, Minimum, Covering, and More","created":"2024-05-14","cited_by_count":7,"area":null},{"id":"2409.02135","title":"Optimization by Parallel Quasi-Quantum Annealing with Gradient-Based Sampling","created":"2024-09-02","cited_by_count":7,"area":null},{"id":"2409.17500","title":"GLinSAT: The General Linear Satisfiability Neural Network Layer By Accelerated Gradient Descent","created":"2024-09-26","cited_by_count":7,"area":null},{"id":"2503.04047","title":"Reheated Gradient-based Discrete Sampling for Combinatorial Optimization","created":"2025-03-06","cited_by_count":6,"area":null},{"id":"2211.07767","title":"Learning to Optimize with Stochastic Dominance Constraints","created":"2022-11-14","cited_by_count":5,"area":null},{"id":"2307.00783","title":"Monte Carlo Policy Gradient Method for Binary Optimization","created":"2023-07-03","cited_by_count":5,"area":null},{"id":"2310.05309","title":"Optimizing Solution-Samplers for Combinatorial Problems: The Landscape of Policy-Gradient Methods","created":"2023-10-08","cited_by_count":5,"area":null},{"id":"2310.18672","title":"Maximum Independent Set: Self-Training through Dynamic Programming","created":"2023-10-28","cited_by_count":5,"area":null},{"id":"2406.13125","title":"A Unified Framework for Combinatorial Optimization Based on Graph Neural Networks","created":"2024-06-19","cited_by_count":5,"area":null},{"id":"2111.00463","title":"FastCover: An Unsupervised Learning Framework for Multi-Hop Influence Maximization in Social Networks","created":"2021-10-31","cited_by_count":4,"area":null},{"id":"2407.16468","title":"Enhancing GNNs Performance on Combinatorial Optimization by Recurrent Feature Update","created":"2024-07-23","cited_by_count":4,"area":null},{"id":"2501.18527","title":"Neural Discovery in Mathematics: Do Machines Dream of Colored Planes?","created":"2025-01-30","cited_by_count":4,"area":null},{"id":"2510.24039","title":"Geometric Algorithms for Neural Combinatorial Optimization with Constraints","created":"2025-10-28","cited_by_count":4,"area":null},{"id":"2206.01008","title":"Approximate Network Motif Mining Via Graph Learning","created":"2022-06-02","cited_by_count":3,"area":null},{"id":"2402.02190","title":"Continuous Parallel Relaxation for Finding Diverse Solutions in Combinatorial Optimization Problems","created":"2024-02-03","cited_by_count":3,"area":null},{"id":"2406.11897","title":"A Benchmark for Maximum Cut: Towards Standardization of the Evaluation of Learned Heuristics for Combinatorial Optimization","created":"2024-06-14","cited_by_count":3,"area":null},{"id":"2502.20632","title":"Lattice Protein Folding with Variational Annealing","created":"2025-02-28","cited_by_count":3,"area":null},{"id":"2403.08757","title":"Efficient Combinatorial Optimization via Heat Diffusion","created":"2024-03-13","cited_by_count":2,"area":null},{"id":"2404.04874","title":"Quadratic Binary Optimization with Graph Neural Networks","created":"2024-04-07","cited_by_count":2,"area":null},{"id":"2405.21023","title":"Compact Optimality Verification for Optimization Proxies","created":"2024-05-31","cited_by_count":2,"area":null},{"id":"2409.04495","title":"Learning to Solve Combinatorial Optimization under Positive Linear Constraints via Non-Autoregressive Neural Networks","created":"2024-09-06","cited_by_count":2,"area":null},{"id":"2508.20330","title":"FORGE: Foundational Optimization Representations from Graph Embeddings","created":"2025-08-28","cited_by_count":2,"area":null},{"id":"2510.22538","title":"Iteratively Refined Early Interaction Alignment for Subgraph Matching based Graph Retrieval","created":"2025-10-26","cited_by_count":2,"area":null},{"id":"2602.18419","title":"Benchmarking Graph Neural Networks in Solving Hard Constraint Satisfaction Problems","created":"2026-02-20","cited_by_count":2,"area":null},{"id":"2211.14405","title":"Learning Branching Heuristics from Graph Neural Networks","created":"2022-11-26","cited_by_count":1,"area":null},{"id":"2306.00717","title":"Graph Neural Networks-Based User Pairing in Wireless Communication Systems","created":"2023-05-14","cited_by_count":1,"area":null},{"id":"2308.00327","title":"Threshold-aware Learning to Generate Feasible Solutions for Mixed Integer Programs","created":"2023-08-01","cited_by_count":1,"area":null},{"id":"2402.07191","title":"GSINA: Improving Subgraph Extraction for Graph Invariant Learning via Graph Sinkhorn Attention","created":"2024-02-11","cited_by_count":1,"area":null},{"id":"2411.05834","title":"Assessing and Enhancing Graph Neural Networks for Combinatorial Optimization: Novel Approaches and Application in Maximum Independent Set Problems","created":"2024-11-06","cited_by_count":1,"area":null},{"id":"2503.21814","title":"Unsupervised Ordering for Maximum Clique","created":"2025-03-25","cited_by_count":1,"area":null},{"id":"2505.19497","title":"Learning for Dynamic Combinatorial Optimization without Training Data","created":"2025-05-26","cited_by_count":1,"area":null},{"id":"2508.01557","title":"Unsupervised Learning for the Elementary Shortest Path Problem","created":"2025-08-03","cited_by_count":1,"area":null},{"id":"2212.00296","title":"Learning Markov Random Fields for Combinatorial Structures via Sampling through Lov\\'asz Local Lemma","created":"2022-12-01","cited_by_count":0,"area":null},{"id":"2302.09512","title":"SAT Requires Exhaustive Search","created":"2023-02-19","cited_by_count":0,"area":null},{"id":"2312.06877","title":"A Novel Differentiable Loss Function for Unsupervised Graph Neural Networks in Graph Partitioning","created":"2023-12-11","cited_by_count":0,"area":null},{"id":"2403.09742","title":"A short review on the maximum clique problem algorithms with classical, AI, and quantum methods","created":"2024-03-13","cited_by_count":0,"area":null},{"id":"2408.08484","title":"An Unsupervised Learning Framework Combined with Heuristics for the Maximum Minimal Cut Problem","created":"2024-08-16","cited_by_count":0,"area":null},{"id":"2410.17111","title":"Permutation Picture of Graph Combinatorial Optimization Problems","created":"2024-10-22","cited_by_count":0,"area":null},{"id":"2502.19377","title":"Preference-Based Gradient Estimation for ML-Guided Approximate Combinatorial Optimization","created":"2025-02-26","cited_by_count":0,"area":null},{"id":"2505.13754","title":"Unsupervised Learning of Local Updates for Maximum Independent Set in Dynamic Graphs","created":"2025-05-19","cited_by_count":0,"area":null},{"id":"2506.16732","title":"On Training-Test (Mis)alignment in Unsupervised Combinatorial Optimization: Observation, Empirical Exploration, and Analysis","created":"2025-06-20","cited_by_count":0,"area":null},{"id":"2507.13703","title":"Binarizing Physics-Inspired GNNs for Combinatorial Optimization","created":"2025-07-18","cited_by_count":0,"area":null},{"id":"2510.01632","title":"BioBlobs: Unsupervised Discovery of Functional Substructures for Protein Function Prediction","created":"2025-10-02","cited_by_count":0,"area":null},{"id":"2511.16374","title":"Unsupervised Graph Neural Network Framework for Balanced Multipatterning in Advanced Electronic Design Automation Layouts","created":"2025-11-20","cited_by_count":0,"area":null},{"id":"2511.22866","title":"ARM-Explainer -- Explaining and improving graph neural network predictions for the maximum clique problem using node features and association rule mining","created":"2025-11-28","cited_by_count":0,"area":null},{"id":"2512.03419","title":"Comparative algorithm performance evaluation and prediction for the maximum clique problem using instance space analysis","created":"2025-12-03","cited_by_count":0,"area":null},{"id":"2512.20915","title":"Towards a General Framework for Predicting and Explaining the Hardness of Graph-based Combinatorial Optimization Problems using Machine Learning and Association Rule Mining","created":"2025-12-24","cited_by_count":0,"area":null},{"id":"2601.18917","title":"GraIP: A Benchmarking Framework For Neural Graph Inverse Problems","created":"2026-01-26","cited_by_count":0,"area":null},{"id":"2601.21048","title":"Test-Time Adaptation for Unsupervised Combinatorial Optimization","created":"2026-01-28","cited_by_count":0,"area":null},{"id":"2602.00302","title":"Neural Ising Machines via Unrolling and Zeroth-Order Training","created":"2026-01-30","cited_by_count":0,"area":null},{"id":"2602.13155","title":"Learning to Approximate Uniform Facility Location via Graph Neural Networks","created":"2026-02-13","cited_by_count":0,"area":null},{"id":"2603.02462","title":"Can Computational Reducibility Lead to Transferable Models for Graph Combinatorial Optimization?","created":"2026-03-02","cited_by_count":0,"area":null},{"id":"2603.11456","title":"UniHetCO: A Unified Heterogeneous Representation for Multi-Problem Learning in Unsupervised Neural Combinatorial Optimization","created":"2026-03-12","cited_by_count":0,"area":null},{"id":"2604.23921","title":"Crystal structure prediction using graph neural combinatorial optimization","created":"2026-04-27","cited_by_count":0,"area":null},{"id":"2605.05330","title":"Graph Normalization: Fast Binarizing Dynamics for Differentiable MWIS","created":"2026-05-06","cited_by_count":0,"area":null},{"id":"2605.19721","title":"Projecting Latent RL Actions: Towards Generalizable and Scalable Graph Combinatorial Optimization","created":"2026-05-19","cited_by_count":0,"area":null},{"id":"2606.14022","title":"Placing Degree Scales After LayerNorm","created":"2026-06-12","cited_by_count":0,"area":null},{"id":"2607.01185","title":"Neural Certificate Pricing for Combinatorial Optimization Problems","created":"2026-07-01","cited_by_count":0,"area":null},{"id":"2607.16769","title":"On the Potential of Graph Neural Networks as Metamodels for Supply Chain Optimization: Dataset, Architectures, and Directions","created":"2026-07-18","cited_by_count":0,"area":null},{"id":"2608.21485","title":"Congruence Decomposition with Neural Block Solvers for Large-Scale PCI Assignment","created":"2026-08-21","cited_by_count":0,"area":null},{"id":"2609.07456","title":"Graph neural networks and the energetic cavity method for combinatorial optimization","created":"2026-09-07","cited_by_count":0,"area":null},{"id":"2609.13836","title":"Graph Neural Networks for Influence Maximization in Social Networks: An Unsupervised Minimum Dominating Set Approach","created":"2026-09-12","cited_by_count":0,"area":null},{"id":"2609.25149","title":"Dual-GNN Multilevel Coarsening for Maximum Independent Set","created":"2026-09-21","cited_by_count":0,"area":null},{"id":"2609.25728","title":"Self-Supervised Combinatorial Optimization with Constraints via Frank-Wolfe","created":"2026-09-22","cited_by_count":0,"area":null}],"next_cursor":null}