Search Results for author: Masayuki Ohzeki

Found 16 papers, 1 papers with code

Kernel-based framework to estimate deformations of pneumothorax lung using relative position of anatomical landmarks

no code implementations24 Feb 2021 Utako Yamamoto, Megumi Nakao, Masayuki Ohzeki, Junko Tokuno, Toyofumi Fengshi Chen-Yoshikawa, Tetsuya Matsuda

In video-assisted thoracoscopic surgeries, successful procedures of nodule resection are highly dependent on the precise estimation of lung deformation between the inflated lung in the computed tomography (CT) images during preoperative planning and the deflated lung in the treatment views during surgery.

Computed Tomography (CT)

Probing the Universality of Topological Defect Formation in a Quantum Annealer: Kibble-Zurek Mechanism and Beyond

no code implementations31 Jan 2020 Yuki Bando, Yuki Susa, Hiroki Oshiyama, Naokazu Shibata, Masayuki Ohzeki, Fernando Javier Gómez-Ruiz, Daniel A. Lidar, Adolfo del Campo, Sei Suzuki, Hidetoshi Nishimori

We find that the degree of agreement with the experimental data from the D-Wave devices is better for the KZM, a quantum theory, than for the classical spin-vector Monte Carlo model, thus favoring a quantum description of the device.

Quantum Physics Statistical Mechanics

Message-passing algorithm of quantum annealing with nonstoquastic Hamiltonian

no code implementations21 Jan 2019 Masayuki Ohzeki

Hence, we developed a system with a time-dependent Hamiltonian consisting of a combination of the formulated Ising model and the "driver" Hamiltonian with only quantum fluctuation.

Optimization of neural networks via finite-value quantum fluctuations

no code implementations1 Jul 2018 Masayuki Ohzeki, Shuntaro Okada, Masayoshi Terabe, Shinichiro Taguchi

We numerically test an optimization method for deep neural networks (DNNs) using quantum fluctuations inspired by quantum annealing.

Momentum-Space Renormalization Group Transformation in Bayesian Image Modeling by Gaussian Graphical Model

no code implementations20 Mar 2018 Kazuyuki Tanaka, Masamichi Nakamura, Shun Kataoka, Masayuki Ohzeki, Muneki Yasuda

A new Bayesian modeling method is proposed by combining the maximization of the marginal likelihood with a momentum-space renormalization group transformation for Gaussian graphical models.

Deep Neural Network Detects Quantum Phase Transition

no code implementations1 Dec 2017 Shunta Arai, Masayuki Ohzeki, Kazuyuki Tanaka

We detect the quantum phase transition of a quantum many-body system by mapping the observed results of the quantum state onto a neural network.

Deformation estimation of an elastic object by partial observation using a neural network

no code implementations28 Nov 2017 Utako Yamamoto, Megumi Nakao, Masayuki Ohzeki, Tetsuya Matsuda

Deformation estimation of elastic object assuming an internal organ is important for the computer navigation of surgery.

Sparse modeling approach to analytical continuation of imaginary-time quantum Monte Carlo data

no code implementations10 Feb 2017 Junya Otsuki, Masayuki Ohzeki, Hiroshi Shinaoka, Kazuyoshi Yoshimi

A new approach of solving the ill-conditioned inverse problem for analytical continuation is proposed.

Compressing Green's function using intermediate representation between imaginary-time and real-frequency domains

1 code implementation10 Feb 2017 Hiroshi Shinaoka, Junya Otsuki, Masayuki Ohzeki, Kazuyoshi Yoshimi

New model-independent compact representations of imaginary-time data are presented in terms of the intermediate representation (IR) of analytical continuation.

Quantum Monte Carlo simulation of a particular class of non-stoquastic Hamiltonians in quantum annealing

no code implementations14 Dec 2016 Masayuki Ohzeki

Quantum annealing is a generic solver of the optimization problem that uses fictitious quantum fluctuation.

Stochastic gradient method with accelerated stochastic dynamics

no code implementations19 Nov 2015 Masayuki Ohzeki

In this study, we propose violating the detailed balance condition to enhance the mixing rate.

L_1-regularized Boltzmann machine learning using majorizer minimization

no code implementations11 Mar 2015 Masayuki Ohzeki

In this study, we utilize the majorizer minimization method, which is a well-known technique implemented in optimization problems, to avoid the non-smoothness of the cost function.

BIG-bench Machine Learning

Statistical-mechanical analysis of pre-training and fine tuning in deep learning

no code implementations19 Jan 2015 Masayuki Ohzeki

In this sense, we evaluate the efficacy of the unsupervised learning component of deep learning.

Inverse Renormalization Group Transformation in Bayesian Image Segmentations

no code implementations5 Jan 2015 Kazuyuki Tanaka, Shun Kataoka, Muneki Yasuda, Masayuki Ohzeki

A new Bayesian image segmentation algorithm is proposed by combining a loopy belief propagation with an inverse real space renormalization group transformation to reduce the computational time.

Image Segmentation Semantic Segmentation

Detection of cheating by decimation algorithm

no code implementations14 Oct 2014 Shogo Yamanaka, Masayuki Ohzeki, Aurelien Decelle

In this paper we aim to infer the correct biases and interactions of our model by considering a relatively small number of sets of training data.

BIG-bench Machine Learning

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