Bayesian Estimation for Mixture of Sparse Linear Regression Model for Exploring New Materials Design Conditions

Tomoya Hirakawa

Presentation information

Oral Session

A. New Materials Methodology for Next-Generation » [A-2] Materials Integration: Prediction and Design for Structural Materials through Data Science

[A2-O4] Slot 04

Tue. Dec 14, 2021 1:30 PM - 3:30 PM Room P (G317)

Chair: Junya Inoue (The University of Tokyo)

3:10 PM - 3:25 PM

[A2-O4-07] Bayesian Estimation for Mixture of Sparse Linear Regression Model for Exploring New Materials Design Conditions

*Tomoya Hirakawa¹, Kyosuke Matsudaira¹, Kenji Nagata², Junya Inoue¹, Manabu Enoki¹, Masato Okada¹ (1. The Univ. of Tokyo (Japan), 2. National Inst. for Materials Sci. (NIMS) (Japan))

Keywords:Uncertainty quantification, Sparse modeling, Mixture of linear regression, Bayesian estimation, Exchange Monte Carlo method

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