Integral representation of the global minimizer. - Sho Sonoda; Isao Ishikawa; Masahiro Ikeda; Kei Hagihara; Yoshihiro Sawano; Takuo Matsubara; Noboru Murata (CoRR, 2018)

The Ridgelet Prior: A Covariance Function Approach to Prior Specification for Bayesian Neural Networks. - Takuo Matsubara; Chris J. Oates; François-Xavier Briol (J. Mach. Learn. Res., 2021)

TCE: A Test-Based Approach to Measuring Calibration Error. - Takuo Matsubara; Niek Tax; Richard Mudd; Ido Guy (UAI, 2023)

Wasserstein Gradient Boosting: A Framework for Distribution-Valued Supervised Learning. - Takuo Matsubara (NeurIPS, 2024)

Wasserstein Gradient Boosting: A General Framework with Applications to Posterior Regression. - Takuo Matsubara (CoRR, 2024)