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06/22/2019
Model Bridging: To Interpretable Simulation Model From Neural Network
The interpretability of machine learning, particularly for deep neural n...
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09/21/2018
Intractable Likelihood Regression for Covariate Shift by Kernel Mean Embedding
Simulation plays an essential role in comprehending a target system in m...
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02/23/2018
Kernel Recursive ABC: Point Estimation with Intractable Likelihood
We propose a novel approach to parameter estimation for simulator-based ...
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07/13/2016
Effects of Additional Data on Bayesian Clustering
Hierarchical probabilistic models, such as mixture models, are used for ...
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10/05/2015
Bayesian Estimation of Multidimensional Latent Variables and Its Asymptotic Accuracy
Hierarchical learning models, such as mixture models and Bayesian networ...
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08/09/2013
Accuracy of Latent-Variable Estimation in Bayesian Semi-Supervised Learning
Hierarchical probabilistic models, such as Gaussian mixture models, are ...
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10/19/2012
Stochastic complexity of Bayesian networks
Bayesian networks are now being used in enormous fields, for example, di...
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05/15/2012
Asymptotic Accuracy of Bayes Estimation for Latent Variables with Redundancy
Hierarchical parametric models consisting of observable and latent varia...
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04/10/2012
