Stochastic complexities of hidden Markov models. - Keisuke Yamazaki; Sumio Watanabe (NNSP, 2003)

Stochastic Complexity of Bayesian Networks. - Keisuke Yamazaki; Sumio Watanabe (UAI, 2003)

Singularities in mixture models and upper bounds of stochastic complexity. - Keisuke Yamazaki; Sumio Watanabe (Neural Networks, 2003)

Newton Diagram and Stochastic Complexity in Mixture of Binomial Distributions. - Keisuke Yamazaki; Sumio Watanabe (ALT, 2004)

Algebraic geometry and stochastic complexity of hidden Markov models. - Keisuke Yamazaki; Sumio Watanabe (Neurocomputing, 2005)

Singularities in complete bipartite graph-type Boltzmann machines and upper bounds of stochastic complexities. - Keisuke Yamazaki; Sumio Watanabe (IEEE Trans. Neural Networks, 2005)

A Model Selection Method Based on Bound of Learning Coefficient. - Keisuke Yamazaki; Kenji Nagata; Sumio Watanabe; Klaus-Robert Müller (ICANN (2), 2006)

Asymptotic Bayesian generalization error when training and test distributions are different. - Keisuke Yamazaki; Motoaki Kawanabe; Sumio Watanabe; Masashi Sugiyama; Klaus-Robert Müller (ICML, 2007)

Experimental Bayesian Generalization Error of Non-regular Models under Covariate Shift. - Keisuke Yamazaki; Sumio Watanabe (ICONIP (1), 2007)

An Analysis of Generalization Error in Relevant Subtask Learning. - Keisuke Yamazaki; Samuel Kaski (ICONIP (1), 2008)

A Study on Bayesian Learning of One-Dimensional Linear Dynamical Systems. - Takuto Naito; Keisuke Yamazaki (ICONIP (1), 2009)

Asymptotic analysis of Bayesian generalization error with Newton diagram. - Keisuke Yamazaki; Miki Aoyagi; Sumio Watanabe (Neural Networks, 2010)

An asymptotic analysis of Bayesian state estimation in hidden Markov models. - Keisuke Yamazaki (MLSP, 2011)

Parameter estimation accuracy and active learning in the zero-range process. - Koichi Kobayashi; Keisuke Yamazaki (ISDA, 2012)

Accuracy of latent variable estimation with the maximum likelihood estimator for partially observed hidden data. - Keisuke Yamazaki (ISITA, 2012)

MCMC sampling on latent-variable space of mixture of probabilistic PCA. - Keisuke Yamazaki (SCIS&ISIS, 2012)

On equivalent parameter learning in simplified feature space based on Bayesian asymptotic analysis. - Keisuke Yamazaki (Neural Networks, 2012)

A Geometric Evaluation of Self-Organizing Map and Application to City Data Analysis. - Shigehiro Ohara; Keisuke Yamazaki; Sumio Watanabe (MIWAI, 2013)

Comparing two Bayes methods based on the free energy functions in Bernoulli mixtures. - Keisuke Yamazaki; Daisuke Kaji (Neural Networks, 2013)

Two statistical methods for grouping vehicles in traffic flow based on probabilistic cellular automata. - Fumito Nakamura; Keisuke Yamazaki (SCIS&ISIS, 2014)

The optimal hyperparameter for Bayesian clustering and its application to the evaluation of clustering results. - Keisuke Yamazaki (SCIS&ISIS, 2014)

Asymptotic Marginal Likelihood on Linear Dynamical Systems. - Takuto Naito; Keisuke Yamazaki (IEICE Trans. Inf. Syst., 2014)

On Bayesian Clustering with a Structured Gaussian Mixture. - Keisuke Yamazaki (J. Adv. Comput. Intell. Intell. Informatics, 2014)

Asymptotic accuracy of distribution-based estimation of latent variables. - Keisuke Yamazaki (J. Mach. Learn. Res., 2014)

Accuracy analysis of semi-supervised classification when the class balance changes. - Keisuke Yamazaki (Neurocomputing, 2015)

On the Optimal Hyperparameter Behavior in Bayesian Clustering. - Keisuke Yamazaki (J. Adv. Comput. Intell. Intell. Informatics, 2015)

Accuracy of latent-variable estimation in Bayesian semi-supervised learning. - Keisuke Yamazaki (Neural Networks, 2015)

Asymptotic accuracy of Bayesian estimation for a single latent variable. - Keisuke Yamazaki (Neural Networks, 2015)

Asymptotic accuracy of Bayes estimation for latent variables with redundancy. - Keisuke Yamazaki (Mach. Learn., 2016)

Hidden Node Detection between Two Observable Nodes Based on Bayesian Clustering. - Keisuke Yamazaki; Yoichi Motomura (AMBN, 2017)

A Risk Information Provision System on Bicycle Parking Lots. - Keisuke Yamazaki; Tsuyoshi Nakajima (ICIOT, 2017)

Effects of additional data on Bayesian clustering. - Keisuke Yamazaki (Neural Networks, 2017)

Kernel Recursive ABC: Point Estimation with Intractable Likelihood. - Takafumi Kajihara; Motonobu Kanagawa; Keisuke Yamazaki; Kenji Fukumizu (ICML, 2018)

Intractable Likelihood Regression for Covariate Shift by Kernel Mean Embedding. - Keiichi Kisamori; Keisuke Yamazaki (CoRR, 2018)

Bayesian estimation of multidimensional latent variables and its asymptotic accuracy. - Keisuke Yamazaki (Neural Networks, 2018)

Model Bridging: To Interpretable Simulation Model From Neural Network. - Keiichi Kisamori; Keisuke Yamazaki (CoRR, 2019)

Hidden Node Detection between Observable Nodes Based on Bayesian Clustering. - Keisuke Yamazaki; Yoichi Motomura (Entropy, 2019)

Simulator Calibration under Covariate Shift with Kernels. - Keiichi Kisamori; Motonobu Kanagawa; Keisuke Yamazaki (AISTATS, 2020)

Model Bridging: Connection Between Simulation Model and Neural Network. - Keiichi Kisamori; Keisuke Yamazaki; Yuto Komori; Hiroshi Tokieda (ECML/PKDD (5), 2020)

Conditional Drive Environment Translation using StarGAN with CBIN. - Rina Komatsu; Keisuke Yamazaki (AICCC, 2021)

Detecting aggressive agents in egress process by using conflict data in cellular automaton model. - Daichi Yanagisawa; Keisuke Yamazaki (J. Intell. Transp. Syst., 2021)

Individual-based epidemiological model of COVID19 using location data. - Yoriyuki Yamagata; Shunki Takami; Keisuke Yamazaki; Tomoki Nakaya; Masaki Onishi (IEEE Big Data, 2022)

Visual-only Voice Activity Detection using Human Motion in Conference Video. - Keisuke Yamazaki; Satoshi Tamura; Yuuto Gotoh; Masaki Nose (ICPRAM, 2022)

Validation of a Property Estimation Method Based on Sequential and Posteriori Estimation. - Tomoya Kitamura; Atsumi Saito; Keisuke Yamazaki; Yuki Saito 003; Hiroshi Asai; Kouhei Ohnishi (IECON, 2022)

A Geometric Surrogate for Simulation Calibration. - Lincon S. Souza; Bojan Batalo; Keisuke Yamazaki (ICASSP, 2023)

Model Selection Methods for Model-Bridge Simulation Calibration. - Bojan Batalo; Lincon S. Souza; Keisuke Yamazaki (IEEE Access, 2025)