{"total":191,"rows":[{"id":"2107.01188","title":"Combinatorial Optimization with Physics-Inspired Graph Neural Networks","created":"2021-07-02","cited_by_count":108,"area":null},{"id":"2101.08448","title":"Noisy intermediate-scale quantum (NISQ) algorithms","created":"2021-01-21","cited_by_count":79,"area":null},{"id":"2101.10154","title":"Variational Neural Annealing","created":"2021-01-25","cited_by_count":47,"area":null},{"id":"2205.06109","title":"Equivariant quantum circuits for learning on weighted graphs","created":"2022-05-12","cited_by_count":41,"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":"2305.18321","title":"Training an Ising Machine with Equilibrium Propagation","created":"2023-05-22","cited_by_count":29,"area":null},{"id":"2109.05536","title":"Link Scheduling using Graph Neural Networks","created":"2021-09-12","cited_by_count":26,"area":null},{"id":"2311.14156","title":"Variational Annealing on Graphs for Combinatorial Optimization","created":"2023-11-23","cited_by_count":21,"area":null},{"id":"2204.04906","title":"Application of QUBO solver using black-box optimization to structural design for resonance avoidance","created":"2022-04-11","cited_by_count":17,"area":null},{"id":"2309.16965","title":"Controlling Continuous Relaxation for Combinatorial Optimization","created":"2023-09-29","cited_by_count":16,"area":null},{"id":"2110.05089","title":"Feature Selection for Recommender Systems with Quantum Computing","created":"2021-10-11","cited_by_count":14,"area":null},{"id":"2112.11534","title":"Noise-injected analog Ising machines enable ultrafast statistical sampling and machine learning","created":"2021-12-21","cited_by_count":11,"area":null},{"id":"2205.04346","title":"Towards Feature Selection for Ranking and Classification Exploiting Quantum Annealers","created":"2022-05-09","cited_by_count":11,"area":null},{"id":"2311.12912","title":"Q-Seg: Quantum Annealing-Based Unsupervised Image Segmentation","created":"2023-11-21","cited_by_count":11,"area":null},{"id":"2502.00277","title":"Regularized Langevin Dynamics for Combinatorial Optimization","created":"2025-02-01","cited_by_count":10,"area":null},{"id":"2206.11040","title":"Penalty Weights in QUBO Formulations: Permutation Problems","created":"2022-06-20","cited_by_count":9,"area":null},{"id":"2209.01016","title":"Black-box optimization for integer-variable problems using Ising machines and factorization machines","created":"2022-09-01","cited_by_count":8,"area":null},{"id":"2303.01977","title":"Hybrid Approach for Solving Real-World Bin Packing Problem Instances Using Quantum Annealers","created":"2023-03-01","cited_by_count":7,"area":null},{"id":"2405.03419","title":"Automated Metaheuristic Algorithm Design with Autoregressive Learning","created":"2024-05-06","cited_by_count":7,"area":null},{"id":"2501.16986","title":"Generative quantum combinatorial optimization by means of a novel conditional generative quantum eigensolver","created":"2025-01-28","cited_by_count":7,"area":null},{"id":"2203.12497","title":"Quantum-enhanced Markov chain Monte Carlo","created":"2022-03-23","cited_by_count":6,"area":null},{"id":"2207.08189","title":"Supplementing Recurrent Neural Networks with Annealing to Solve Combinatorial Optimization Problems","created":"2022-07-17","cited_by_count":6,"area":null},{"id":"2302.00892","title":"Quantum Graph Learning: Frontiers and Outlook","created":"2023-02-02","cited_by_count":6,"area":null},{"id":"2403.19758","title":"Quantum Natural Language Processing","created":"2024-03-28","cited_by_count":6,"area":null},{"id":"2404.06225","title":"Message Passing Variational Autoregressive Network for Solving Intractable Ising Models","created":"2024-04-09","cited_by_count":6,"area":null},{"id":"2405.14405","title":"Qubit-efficient Variational Quantum Algorithms for Image Segmentation","created":"2024-05-23","cited_by_count":6,"area":null},{"id":"2110.08614","title":"Deep Learning and Spectral Embedding for Graph Partitioning","created":"2021-10-16","cited_by_count":5,"area":null},{"id":"2510.19544","title":"Demonstrating Real Advantage of Machine-Learning-Enhanced Monte Carlo for Combinatorial Optimization","created":"2025-10-22","cited_by_count":5,"area":null},{"id":"2110.02142","title":"Lossy compression of statistical data using quantum annealer","created":"2021-10-05","cited_by_count":4,"area":null},{"id":"2202.09506","title":"From Quantum Graph Computing to Quantum Graph Learning: A Survey","created":"2022-02-19","cited_by_count":4,"area":null},{"id":"2210.12953","title":"Implementation of Trained Factorization Machine Recommendation System on Quantum Annealer","created":"2022-10-24","cited_by_count":4,"area":null},{"id":"2210.17037","title":"FrozenQubits: Boosting Fidelity of QAOA by Skipping Hotspot Nodes","created":"2022-10-31","cited_by_count":4,"area":null},{"id":"2303.14993","title":"Low-rank combinatorial optimization and statistical learning by spatial photonic Ising machine","created":"2023-03-27","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":"2408.03076","title":"Solving QUBO on the Loihi 2 Neuromorphic Processor","created":"2024-08-06","cited_by_count":4,"area":null},{"id":"2409.18692","title":"MG-Net: Learn to Customize QAOA with Circuit Depth Awareness","created":"2024-09-27","cited_by_count":4,"area":null},{"id":"2507.21024","title":"SWIFT-FMQA: Enhancing Factorization Machine with Quadratic-Optimization Annealing via Sliding Window","created":"2025-07-28","cited_by_count":4,"area":null},{"id":"2102.05919","title":"Focusing on the Hybrid Quantum Computing -- Tabu Search Algorithm: new results on the Asymmetric Salesman Problem","created":"2021-02-11","cited_by_count":3,"area":null},{"id":"2112.10219","title":"Quantum Approximate Optimization Algorithm applied to the binary perceptron","created":"2021-12-19","cited_by_count":3,"area":null},{"id":"2205.13399","title":"Multi-objective QUBO Solver: Bi-objective Quadratic Assignment","created":"2022-05-26","cited_by_count":3,"area":null},{"id":"2206.12510","title":"Black Box Optimization Using QUBO and the Cross Entropy Method","created":"2022-06-24","cited_by_count":3,"area":null},{"id":"2209.03788","title":"Quantum Sparse Coding","created":"2022-09-08","cited_by_count":3,"area":null},{"id":"2211.02861","title":"Feature Selection for Classification with QAOA","created":"2022-11-05","cited_by_count":3,"area":null},{"id":"2305.16656","title":"Clustering Method for Time-Series Images Using Quantum-Inspired Computing Technology","created":"2023-05-26","cited_by_count":3,"area":null},{"id":"2310.15128","title":"Projected Stochastic Gradient Descent with Quantum Annealed Binary Gradients","created":"2023-10-23","cited_by_count":3,"area":null},{"id":"2311.03408","title":"Training Multi-layer Neural Networks on Ising Machine","created":"2023-11-06","cited_by_count":3,"area":null},{"id":"2403.03391","title":"CoRMF: Criticality-Ordered Recurrent Mean Field Ising Solver","created":"2024-03-05","cited_by_count":3,"area":null},{"id":"2403.18908","title":"Enhancing Multiple Object Tracking Accuracy via Quantum Annealing","created":"2024-03-27","cited_by_count":3,"area":null},{"id":"2102.12534","title":"Entanglement Diagnostics for Efficient Quantum Computation","created":"2021-02-24","cited_by_count":2,"area":null},{"id":"2103.10695","title":"QROSS: QUBO Relaxation Parameter Optimisation via Learning Solver Surrogates","created":"2021-03-19","cited_by_count":2,"area":null},{"id":"2106.00065","title":"Using machine learning for quantum annealing accuracy prediction","created":"2021-05-31","cited_by_count":2,"area":null},{"id":"2107.11695","title":"Efficient QUBO transformation for Higher Degree Pseudo Boolean Functions","created":"2021-07-24","cited_by_count":2,"area":null},{"id":"2208.03082","title":"Conflict-free joint sampling for preference satisfaction through quantum interference","created":"2022-08-05","cited_by_count":2,"area":null},{"id":"2211.15869","title":"Fast Hyperparameter Tuning for Ising Machines","created":"2022-11-29","cited_by_count":2,"area":null},{"id":"2212.01312","title":"Hybrid adiabatic quantum computing for tomographic image reconstruction -- opportunities and limitations","created":"2022-12-02","cited_by_count":2,"area":null},{"id":"2304.11839","title":"Local Energy Distribution Based Hyperparameter Determination for Stochastic Simulated Annealing","created":"2023-04-24","cited_by_count":2,"area":null},{"id":"2307.06542","title":"Quantum Image Denoising: A Framework via Boltzmann Machines, QUBO, and Quantum Annealing","created":"2023-07-13","cited_by_count":2,"area":null},{"id":"2308.01789","title":"Benchmarking Adaptative Variational Quantum Algorithms on QUBO Instances","created":"2023-08-03","cited_by_count":2,"area":null},{"id":"2311.13546","title":"Enigma: Application-Layer Privacy for Quantum Optimization on Untrusted Computers","created":"2023-11-22","cited_by_count":2,"area":null},{"id":"2312.12848","title":"Quantum Annealing for Computer Vision Minimization Problems","created":"2023-12-20","cited_by_count":2,"area":null},{"id":"2403.08757","title":"Efficient Combinatorial Optimization via Heat Diffusion","created":"2024-03-13","cited_by_count":2,"area":null},{"id":"2409.10863","title":"Dynamic Range Reduction via Branch-and-Bound","created":"2024-09-17","cited_by_count":2,"area":null},{"id":"2409.18631","title":"Quantum Algorithms for Drone Mission Planning","created":"2024-09-27","cited_by_count":2,"area":null},{"id":"2410.14093","title":"Enhancing In-vehicle Multiple Object Tracking Systems with Embeddable Ising Machines","created":"2024-10-18","cited_by_count":2,"area":null},{"id":"2502.07192","title":"OscNet: Machine Learning on CMOS Oscillator Networks","created":"2025-02-11","cited_by_count":2,"area":null},{"id":"2506.16924","title":"Real-Time Black-Box Optimization for Dynamic Discrete Environments Using Embedded Ising Machines","created":"2025-06-20","cited_by_count":2,"area":null},{"id":"2508.17440","title":"Programmable k-local Ising interactions and shallow optical Kolmogorov--Arnold networks through repeated data encounters","created":"2025-08-24","cited_by_count":2,"area":null},{"id":"2510.16075","title":"Optimization of the quantization of dense neural networks from an exact QUBO formulation","created":"2025-10-17","cited_by_count":2,"area":null},{"id":"2512.07766","title":"Formalized Hopfield Networks and Boltzmann Machines","created":"2025-12-08","cited_by_count":2,"area":null},{"id":"2205.01698","title":"On Circuit Depth Scaling For Quantum Approximate Optimization","created":"2022-05-03","cited_by_count":1,"area":null},{"id":"2205.13586","title":"Comparing the Digital Annealer with Classical Evolutionary Algorithm","created":"2022-05-26","cited_by_count":1,"area":null},{"id":"2207.00253","title":"Analyzing the behaviour of D'WAVE quantum annealer: fine-tuning parameterization and tests with restrictive Hamiltonian formulations","created":"2022-07-01","cited_by_count":1,"area":null},{"id":"2210.10662","title":"Towards Practical Explainability with Cluster Descriptors","created":"2022-10-18","cited_by_count":1,"area":null},{"id":"2307.15778","title":"Spherical and Hyperbolic Toric Topology-Based Codes On Graph Embedding for Ising MRF Models: Classical and Quantum Topology Machine Learning","created":"2023-07-28","cited_by_count":1,"area":null},{"id":"2309.09736","title":"An Optimization Case Study for solving a Transport Robot Scheduling Problem on Quantum-Hybrid and Quantum-Inspired Hardware","created":"2023-09-18","cited_by_count":1,"area":null},{"id":"2309.12678","title":"QAL-BP: An Augmented Lagrangian Quantum Approach for Bin Packing","created":"2023-09-22","cited_by_count":1,"area":null},{"id":"2311.02101","title":"Solving MaxSAT with Matrix Multiplication","created":"2023-11-01","cited_by_count":1,"area":null},{"id":"2403.05764","title":"Investigation into the Potential of Parallel Quantum Annealing for Simultaneous Optimization of Multiple Problems: A Comprehensive Study","created":"2024-03-09","cited_by_count":1,"area":null},{"id":"2407.02091","title":"Efficient Bit Labeling in Factorization Machines with Annealing for Traveling Salesman Problem","created":"2024-07-02","cited_by_count":1,"area":null},{"id":"2408.00570","title":"Analyzing the Effectiveness of Quantum Annealing with Meta-Learning","created":"2024-08-01","cited_by_count":1,"area":null},{"id":"2412.02759","title":"Mixture of Physical Priors Adapter for Parameter-Efficient Fine-Tuning","created":"2024-12-03","cited_by_count":1,"area":null},{"id":"2412.18571","title":"Scalable Quantum-Inspired Optimization through Dynamic Qubit Compression","created":"2024-12-24","cited_by_count":1,"area":null},{"id":"2412.19284","title":"PearSAN: A Machine Learning Method for Inverse Design using Pearson Correlated Surrogate Annealing","created":"2024-12-26","cited_by_count":1,"area":null},{"id":"2412.21071","title":"Investigating layer-selective transfer learning of QAOA parameters for Max-Cut problem","created":"2024-12-30","cited_by_count":1,"area":null},{"id":"2501.02114","title":"Relaxation-assisted reverse annealing on nonnegative/binary matrix factorization","created":"2025-01-03","cited_by_count":1,"area":null},{"id":"2501.04971","title":"Self-Adaptive Ising Machines for Constrained Optimization","created":"2025-01-09","cited_by_count":1,"area":null},{"id":"2501.14120","title":"On the Transfer of Knowledge in Quantum Algorithms","created":"2025-01-23","cited_by_count":1,"area":null},{"id":"2501.14568","title":"Hybrid Quantum-Classical Multi-Agent Pathfinding","created":"2025-01-24","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":"2506.14781","title":"Two-dimensional Parallel Tempering for Constrained Optimization","created":"2025-05-24","cited_by_count":1,"area":null},{"id":"2507.15063","title":"Quantum Annealing for Machine Learning: Applications in Feature Selection, Instance Selection, and Clustering","created":"2025-07-20","cited_by_count":1,"area":null},{"id":"2508.08778","title":"Subsampling Factorization Machine Annealing","created":"2025-08-12","cited_by_count":1,"area":null},{"id":"2509.00341","title":"Solving Conic Programs over Sparse Graphs using a Variational Quantum Approach: The Case of the AC Optimal Power Flow","created":"2025-08-30","cited_by_count":1,"area":null},{"id":"2509.26229","title":"Hybrid Quantum-Classical Optimisation of Traveling Salesperson Problem","created":"2025-09-30","cited_by_count":1,"area":null},{"id":"2511.00746","title":"Correspondence Between Ising Machines and Neural Networks","created":"2025-11-02","cited_by_count":1,"area":null},{"id":"2603.24298","title":"SpinGQE: A Generative Quantum Eigensolver for Spin Hamiltonians","created":"2026-03-25","cited_by_count":1,"area":null},{"id":"2604.05042","title":"Energy-Based Dynamical Models for Neurocomputation, Learning, and Optimization","created":"2026-04-06","cited_by_count":1,"area":null},{"id":"2605.13072","title":"Neural QAOA$^{2}$: Differentiable Joint Graph Partitioning and Parameter Initialization for Quantum Combinatorial Optimization","created":"2026-05-13","cited_by_count":1,"area":null},{"id":"2605.20222","title":"Quantum End-to-End Learning for Contextual Combinatorial Optimization","created":"2026-05-13","cited_by_count":1,"area":null},{"id":"2609.04593","title":"GNN-Guided Graph Coarsening and Adaptive QUBO Penalties for the Capacitated Vehicle Routing Problem with Time Windows on a Quantum Annealer","created":"2026-09-04","cited_by_count":1,"area":null}],"next_cursor":"100"}