Parameter Estimation for Gaussian Process <i>c</i>-Regression Models Based on Marginal Likelihood Maximization

Authors

Institutions

Publication Details

Journal
Journal of Japan Society for Fuzzy Theory and Intelligent Informatics
Published
2025-05-14
DOI
https://doi.org/10.3156/jsoft.37.2_627
Primary Topic
Fault Detection and Control Systems
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Parameter Estimation for Gaussian Process c-Regression Models Based on Marginal Likelihood Maximization

Kaito Takegawa, Yuya Yokoyama, Yukihiro Hamasuna
Journal of Japan Society for Fuzzy Theory and Intelligent Informatics
Fault Detection and Control Systems
article

Parameter Estimation for Gaussian Process c-Regression Models Based on Marginal Likelihood Maximization

Kaito Takegawa, Yuya Yokoyama, Yukihiro Hamasuna
article en

Abstract

No abstract available for this paper.
Journal of Japan Society for Fuzzy Theory and Intelligent InformaticsVol. 37(2)
Kindai University (JP)
Decent work and economic growth
Openalex Percentile: Top 89%
Fault Detection and Control Systems
DOIOpen Access PDFOpenAlex
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Parameter Estimation for Gaussian Process <i>c</i>-Regression Models Based on Marginal Likelihood Maximization — Kaito Takegawa, Yuya Yokoyama, et al. · Journal of Japan Society for Fuzzy Theory and Intelligent Informatics (2025) | TGRS Research Map | TGRS