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Found 6 papers, 0 papers with code
Black-box optimization for integer-variable problems using Ising machines and factorization machines
Ising machines are useful for binary optimization problems because variables can be represented by a single binary variable of Ising machines.
Continuous black-box optimization with quantum annealing and random subspace coding
As QA specializes in optimization of binary problems, a continuous vector has to be encoded to binary, and the solution of QA has to be translated back.
PyQUBO: Python Library for Mapping Combinatorial Optimization Problems to QUBO Form
QUBOs and Ising models formulated using PyQUBO are solvable by Ising machines, including quantum annealing machines.
Combinatorial Optimization
Quantum Physics
Emerging Technologies
Quantum Annealing for Clustering
This paper studies quantum annealing (QA) for clustering, which can be seen as an extension of simulated annealing (SA).
Quantum Annealing for Variational Bayes Inference
This paper presents studies on a deterministic annealing algorithm based on quantum annealing for variational Bayes (QAVB) inference, which can be seen as an extension of the simulated annealing for variational Bayes (SAVB) inference.
Quantum Annealing for Dirichlet Process Mixture Models with Applications to Network Clustering
We developed a new quantum annealing (QA) algorithm for Dirichlet process mixture (DPM) models based on the Chinese restaurant process (CRP).
