1 citations · 1 across the 5 of their papers we have counts for
9 papers
Simulation-free and finite-time diffusion model
Kentaro Kaba, Masayuki Ohzeki, Yuki Sughiyama
The performance of generative diffusion models is determined by the choice of the reference diffusion process connecting the empirical and prior distributions. Conventional approac…
Population Annealing as a Discrete-Time Schrödinger Bridge
Masayuki Ohzeki
We present a theoretical framework that reinterprets Population Annealing (PA) through the lens of the discrete-time Schrödinger Bridge (SB) problem. We demonstrate that the heuri…
Quantum generative model on bicycle-sharing system and an application
Fumio Nemoto, Nobuyuki Koike, Daichi Sato +2
Recently, bicycle-sharing systems have been implemented in numerous cities, becoming integral to daily life. However, a prevalent issue arises when intensive commuting demand leads…
Kernel Learning for Regression via Quantum Annealing Based Spectral Sampling
Yasushi Hasegawa, Masayuki Ohzeki
While quantum annealing (QA) has been developed for combinatorial optimization, practical QA devices operate at finite temperature and under noise, and their outputs can be regarde…
Storage capacity of perceptron with variable selection
Yingying Xu, Masayuki Ohzeki, Yoshiyuki Kabashima
A central challenge in machine learning is to distinguish genuine structure from chance correlations in high-dimensional data. In this work, we address this issue for the perceptro…
Performance Evaluation of Ising and QUBO Variable Encodings in Boltzmann Machine Learning
Yasushi Hasegawa, Masayuki Ohzeki
We compare Ising ({-1,+1}) and QUBO ({0,1}) encodings for Boltzmann machine learning under a controlled protocol that fixes the model, sampler, and step size. Exploiting the identi…