Keisuke Yamazaki

Bayesian Estimation of Multidimensional Latent Variables and Its Asymptotic Accuracy

2015 · arXiv (Cornell University)

Hierarchical learning models, such as mixture models and Bayesian networks, are widely employed for unsupervised learning tasks, such as clustering analysis. They consist of observable and hidden variables, which represent the given data and their …

Model Bridging: To Interpretable Simulation Model From Neural Network.

2019 · arXiv (Cornell University)

The interpretability of machine learning, particularly for deep neural networks, is strongly required when performing decision-making in a real-world application. There are several studies that show that interpretability is obtained by replacing a non-explainable neural …