Statistical Inferences by Gaussian Markov Random Fields on Complex Networks. - Kazuyuki Tanaka; Takafumi Usui; Muneki Yasuda (CIMCA/IAWTIC/ISE, 2008)

Approximate Learning Algorithm for Restricted Boltzmann Machines. - Muneki Yasuda; Kazuyuki Tanaka (CIMCA/IAWTIC/ISE, 2008)

Approximate Learning Algorithm in Boltzmann Machines. - Muneki Yasuda; Kazuyuki Tanaka (Neural Comput., 2009)

Belief Propagation Algorithm for Portfolio Optimization Problems - Takashi Shinzato; Muneki Yasuda (CoRR, 2010)

Composite likelihood estimation for restricted Boltzmann machines. - Muneki Yasuda; Shun Kataoka; Yuji Waizumi; Kazuyuki Tanaka (ICPR, 2012)

Traffic data reconstruction based on Markov random field modeling. - Shun Kataoka; Muneki Yasuda; Cyril Furtlehner; Kazuyuki Tanaka (CoRR, 2013)

Effective Mean-Field Inference Method for Nonnegative Boltzmann Machines. - Muneki Yasuda (ICPR, 2014)

Estimation of priors in natural images. - Tomoyuki Obuchi; Hirokazu Koma; Muneki Yasuda (CoRR, 2014)

Bayesian image segmentations by Potts prior and loopy belief propagation. - Kazuyuki Tanaka; Shun Kataoka; Muneki Yasuda; Yuji Waizumi; Chiou-Ting Hsu (CoRR, 2014)

Inverse Renormalization Group Transformation in Bayesian Image Segmentations. - Kazuyuki Tanaka; Shun Kataoka; Muneki Yasuda; Masayuki Ohzeki (CoRR, 2015)

Statistical Analysis of Loopy Belief Propagation based on Replica Cluster Variation Method. - Muneki Yasuda; Shun Kataoka; Kazuyuki Tanaka (CoRR, 2015)

Relationship between PreTraining and Maximum Likelihood Estimation in Deep Boltzmann Machines. - Muneki Yasuda (AISTATS, 2016)

Community Detection Algorithm Combining Stochastic Block Model and Attribute Data Clustering. - Shun Kataoka; Takuto Kobayashi; Muneki Yasuda; Kazuyuki Tanaka (CoRR, 2016)

Solving Non-parametric Inverse Problem in Continuous Markov Random Field using Loopy Belief Propagation. - Muneki Yasuda; Shun Kataoka (CoRR, 2017)

Learning Algorithm of Boltzmann Machine Based on Spatial Monte Carlo Integration Method. - Muneki Yasuda (Algorithms, 2018)

Momentum-Space Renormalization Group Transformation in Bayesian Image Modeling by Gaussian Graphical Model. - Kazuyuki Tanaka; Masamichi Nakamura; Shun Kataoka; Masayuki Ohzeki; Muneki Yasuda (CoRR, 2018)

Restricted Boltzmann Machine with Multivalued Hidden Variables: a model suppressing over-fitting. - Yuuki Yokoyama; Tomu Katsumata; Muneki Yasuda (CoRR, 2018)

Linear-Time Algorithm in Bayesian Image Denoising based on Gaussian Markov Random Field. - Muneki Yasuda; Junpei Watanabe; Shun Kataoka; Kazuyuki Tanaka (IEICE Trans. Inf. Syst., 2018)

Estimation System of Blood Pressure Variation with Photoplethysmography Signals Using Multiple Regression Analysis and Neural Network. - Seung-Il Cho; Takumi Negishi; Minami Tsuchiya; Muneki Yasuda; Michio Yokoyama (Int. J. Fuzzy Log. Intell. Syst., 2018)

Empirical Bayes Method for Boltzmann Machines. - Muneki Yasuda; Tomoyuki Obuchi (CoRR, 2019)

Improvement of Batch Normalization in Imbalanced Data. - Muneki Yasuda; Seishirou Ueno (CoRR, 2019)

Bayesian Image Denoising with Multiple Noisy Images. - Shun Kataoka; Muneki Yasuda (Rev. Socionetwork Strateg., 2019)

Sublinear Computational Time Modeling by Momentum-Space Renormalization Group Theory in Statistical Machine Learning Procedures. - Kazuyuki Tanaka; Masayuki Ohzeki; Muneki Yasuda (Rev. Socionetwork Strateg., 2019)

Restricted Boltzmann Machine with Multivalued Hidden Variables. - Yuuki Yokoyama; Tomu Katsumata; Muneki Yasuda (Rev. Socionetwork Strateg., 2019)

Multi-layered Discriminative Restricted Boltzmann Machine with Untrained Probabilistic Layer. - Yuri Kanno; Muneki Yasuda (ICPR, 2020)

Consistent Batch Normalization for Weighted Loss in Imbalanced-Data Environment. - Muneki Yasuda; Yeo Xian En; Seishirou Ueno (CoRR, 2020)

Spatial Monte Carlo Integration with Annealed Importance Sampling. - Muneki Yasuda; Kaiji Sekimoto (CoRR, 2020)

Changing Tendency Analysis of Sleep Quality on the Basis of Temperature and Respiratory Frequency Using a Neural Network Model. - Minami Tsuchiya; Seung-Il Cho; Atsushi Tanaka; Muneki Yasuda; Tomochika Harada; Michio Yokoyama (Int. J. Fuzzy Log. Intell. Syst., 2020)

A Generalization of Spatial Monte Carlo Integration. - Muneki Yasuda; Kei Uchizawa (Neural Comput., 2021)

Composite Spatial Monte Carlo Integration Based on Generalized Least Squares. - Kaiji Sekimoto; Muneki Yasuda (CoRR, 2022)

Free Energy Evaluation Using Marginalized Annealed Importance Sampling. - Muneki Yasuda; Chako Takahashi (CoRR, 2022)

Hierarchical Gaussian Markov Random Field for Image Denoising. - Yuki Monma; Kan Aro; Muneki Yasuda (IEICE Trans. Inf. Syst., 2022)

Improving Interpretability of Scores in Anomaly Detection Based on Gaussian-Bernoulli Restricted Boltzmann Machine. - Kaiji Sekimoto; Muneki Yasuda (CoRR, 2024)

Dataset-free weight-initialization on restricted Boltzmann machine. - Muneki Yasuda; Ryosuke Maeno; Chako Takahashi (Neural Networks, 2025)

Effective Method for Inverse Ising Problem under Missing Observations in Restricted Boltzmann Machines. - Kaiji Sekimoto; Muneki Yasuda (CoRR, 2025)