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05/11/2023
Sequential Experimental Design for Spectral Measurement: Active Learning Using a Parametric Model
In this study, we demonstrate a sequential experimental design for spect...
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03/09/2023
Bayesian Inference for Small-Angle Scattering Data
In this paper, we propose a method for estimating model parameters using...
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12/14/2022
Bayesian Spectral Deconvolution Based on Binominal Distribution
When analyzing spectral data, it is effective to use spectral deconvolut...
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03/18/2022
Bayesian Spectral Deconvolution of X-Ray Absorption Near Edge Structure Discriminating High- and Low-Energy Domain
In this paper, we propose a Bayesian spectral deconvolution considering ...
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05/16/2021
Statistical Mechanical Analysis of Catastrophic Forgetting in Continual Learning with Teacher and Student Networks
When a computational system continuously learns from an ever-changing en...
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11/26/2020
Fast Bayesian Deconvolution using Simple Reversible Jump Moves
We propose a Markov chain Monte Carlo-based deconvolution method designe...
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01/10/2020
Data-Dependence of Plateau Phenomenon in Learning with Neural Network — Statistical Mechanical Analysis
The plateau phenomenon, wherein the loss value stops decreasing during t...
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01/05/2020
Emergent limits of an indirect measurement from phase transitions of inference
Measurements are inseparable from inference, where the estimation of sig...
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12/11/2018
Bayesian Spectral Deconvolution Based on Poisson Distribution: Bayesian Measurement and Virtual Measurement Analytics (VMA)
In this paper, we propose a new method of Bayesian measurement for spect...
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05/29/2018
Statistical mechanical analysis of sparse linear regression as a variable selection problem
An algorithmic limit of compressed sensing or related variable-selection...
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12/12/2017
Concept Formation and Dynamics of Repeated Inference in Deep Generative Models
Deep generative models are reported to be useful in broad applications i...
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07/07/2017
Exhaustive search for sparse variable selection in linear regression
We propose a K-sparse exhaustive search (ES-K) method and a K-sparse app...
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06/20/2017
Statistical Mechanics of Node-perturbation Learning with Noisy Baseline
Node-perturbation learning is a type of statistical gradient descent alg...
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07/26/2016
Simultaneous Estimation of Noise Variance and Number of Peaks in Bayesian Spectral Deconvolution
The heuristic identification of peaks from noisy complex spectra often l...
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11/08/2010