4 papers · 1 filter
Generalized Power Priors for Improved Bayesian Inference with Historical Data
Masanari Kimura, Howard Bondell
The power prior is a class of informative priors designed to incorporate historical data alongside current data in a Bayesian framework. It includes a power parameter that controls…
Theoretical and Practical Analysis of Fréchet Regression via Comparison Geometry
Masanari Kimura, Howard Bondell
Fréchet regression extends classical regression methods to non-Euclidean metric spaces, enabling the analysis of data relationships on complex structures such as manifolds and gra…
Test-Time Augmentation Meets Variational Bayes
Masanari Kimura, Howard Bondell
Data augmentation is known to contribute significantly to the robustness of machine learning models. In most instances, data augmentation is utilized during the training phase. Tes…
Density Ratio Estimation via Sampling along Generalized Geodesics on Statistical Manifolds
Masanari Kimura, Howard Bondell
The density ratio of two probability distributions is one of the fundamental tools in mathematical and computational statistics and machine learning, and it has a variety of known…