Cover Image

Correspondence Between Ising Machines and Neural Networks

Fuente: arXiv

Saved in:

Bibliographic Details
Main Author:	Moore, Andrew G.
Format:	Preprint
Published:	2025
Subjects:	Disordered Systems and Neural Networks Emerging Technologies Machine Learning Quantum Physics
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Geometric Theory of Ising Machines
by: Moore, Andrew G., et al.
Published: (2025)

Predicting sampling advantage of stochastic Ising Machines for Quantum Simulations
by: Berns, Rutger J. L. F., et al.
Published: (2025)

Encoding arbitrary Ising Hamiltonians on Spatial Photonic Ising Machines
by: Sakellariou, Jason, et al.
Published: (2024)

Probabilistic Computers for Neural Quantum States
by: Chowdhury, Shuvro, et al.
Published: (2025)

Quantum Equilibrium Propagation for efficient training of quantum systems based on Onsager reciprocity
by: Wanjura, Clara C., et al.
Published: (2024)

Training single-electron and single-photon stochastic physical neural networks
by: Dou, Tong, et al.
Published: (2026)

Efficient Computation Using Spatial-Photonic Ising Machines: Utilizing Low-Rank and Circulant Matrix Constraints
by: Wang, Richard Zhipeng, et al.
Published: (2024)

A Fast Algorithm to Simulate Nonlinear Resistive Networks
by: Scellier, Benjamin
Published: (2024)

Fully Programmable Spatial Photonic Ising Machine by Focal Plane Division
by: Veraldi, Daniele, et al.
Published: (2024)

Probabilistic Computing Optimization of Complex Spin-Glass Topologies
by: Hasselgren, Fredrik, et al.
Published: (2025)

Pushing the Boundary of Quantum Advantage in Hard Combinatorial Optimization with Probabilistic Computers
by: Chowdhury, Shuvro, et al.
Published: (2025)

4-clique Network Minor Embedding for Quantum Annealers
by: Pelofske, Elijah
Published: (2023)

Hybrid Magnonic Reservoir Computing
by: Abbott, Cliff B., et al.
Published: (2024)

Dependence of Equilibrium Propagation Training Success on Network Architecture
by: Wang, Qingshan, et al.
Published: (2026)

Scaling Whole-Chip QAOA for Higher-Order Ising Spin Glass Models on Heavy-Hex Graphs
by: Pelofske, Elijah, et al.
Published: (2023)

Transition from Statistical to Hardware-Limited Scaling in Photonic Quantum State Reconstruction
by: Baumann, Attila, et al.
Published: (2026)

Online unsupervised Hebbian learning in deep photonic neuromorphic networks
by: Li, Xi, et al.
Published: (2026)

Streamlined optical training of large-scale modern deep learning architectures with direct feedback alignment
by: Wang, Ziao, et al.
Published: (2024)

Nonlinear optical encoding enabled by recurrent linear scattering
by: Xia, Fei, et al.
Published: (2023)

Intrinsic Neuro-Synaptic Spiking Dynamics and Resonance in Memristive Networks
by: Xu, Yinhao, et al.
Published: (2026)

Exploring Structural Nonlinearity in Binary Polariton-Based Neuromorphic Architectures
by: Sedov, Evgeny, et al.
Published: (2024)

Highly Versatile FPGA-Implemented Cyber Coherent Ising Machine
by: Aonishi, Toru, et al.
Published: (2024)

Quantum Annealing: Optimisation, Sampling, and Many-Body Dynamics
by: Abel, Steven, et al.
Published: (2026)

Solving Sudoku using oscillatory neural networks
by: Haverkort, Bram F., et al.
Published: (2025)

SPICE Modeling of Memcomputing Logic Gates
by: Pershin, Y. V.
Published: (2023)

Noise-augmented Chaotic Ising Machines for Combinatorial Optimization and Sampling
by: Lee, Kyle, et al.
Published: (2024)

Spatio-temporal evolution of resistance state in simulated memristive networks
by: Di Francesco, Fabrizio, et al.
Published: (2021)

Quest for a solution to drift in phase change memory devices
by: Kersting, Benedikt
Published: (2024)

Brain-like features of MemComputing machines
by: Di Ventra, Massimiliano
Published: (2023)

Coupling Light with Matter for Identifying Dominant Subnetworks
by: Kamaletdinov, Airat, et al.
Published: (2024)

Self-Organising Memristive Networks as Physical Learning Systems
by: Caravelli, Francesco, et al.
Published: (2025)

A fully parallel densely connected probabilistic Ising machine with inertia for real-time applications
by: Zhu, Ruomin, et al.
Published: (2026)

Higher-Order Kuramoto Oscillator Network for Dense Associative Memory
by: Nagerl, Jona, et al.
Published: (2025)

How to Train Your Resistive Network: Generalized Equilibrium Propagation and Analytical Learning
by: Lin, Jonathan, et al.
Published: (2026)

Performance report of heuristic algorithm that cracked the largest Gset Ising problems (G81 cut=14060)
by: Zick, Kenneth M.
Published: (2025)

Dynamic Reservoir Computing with Physical Neuromorphic Networks
by: Xu, Yinhao, et al.
Published: (2025)

Learning Chaotic Dynamics with Neuromorphic Network Dynamics
by: Xu, Yinhao, et al.
Published: (2025)

Spatial QUBO: Convolutional Formulation of Large-Scale Binary Optimization with Dense Interactions
by: Yamashita, Hiroshi, et al.
Published: (2025)

Training and synchronizing oscillator networks with Equilibrium Propagation
by: Rageau, Théophile, et al.
Published: (2025)

Configurable p-Neurons Using Modular p-Bits
by: Bunaiyan, Saleh, et al.
Published: (2026)