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RIKEN Center for Brain Science Statistical Mathematics Collaboration Unit

Unit Leader: Takeru Matsuda (Ph.D.)

Research Summary

Takeru Matsuda

With recent advances in experimental technologies, large-scale and diverse brain data are now available. To extract more information from such brain data, we develop tailored statistical methods by translating the characteristics of data into the form of statistical models. We incorporate techniques from applied mathematics, such as numerical analysis and optimization, to develop efficient methods that are applicable to large-scale data. We also investigate the fundamental theory of statistics.

Main Research Fields

  • Informatics

Related Research Fields

  • Interdisciplinary Science & Engineering
  • Mathematical & Physical Sciences
  • Statistical science
  • Mathematical informatics


  • Statistics
  • Applied mathematics
  • Data analysis
  • Machine learning

Selected Publications

Papers with an asterisk(*) are based on research conducted outside of RIKEN.

  • 1. Matsuda, T. and Strawderman, W. E.
    "Estimation under matrix quadratic loss and matrix superharmonicity"
    Biometrika, to appear.
  • 1. Matsuda, T., Homae. F., Watanabe, H., Taga, G. and Komaki, F.
    "Oscillator decomposition of infant fNIRS data"
    PLOS Computational Biology, 18(3), e1009985, 2022.
  • 2. Amari, S. and Matsuda, T.
    "Wasserstein statistics in one-dimensional location-scale models"
    Annals of the Institute of Statistical Mathematics, 74, 33–47, 2022.
  • 3. Matsuda, T., Uehara, M. and Hyvarinen, A.
    "Information criteria for non-normalized models"
    Journal of Machine Learning Research, 22(158):1−33, 2021.
  • 4. Matsuda. T. and Miyatake, Y.
    "Estimation of ordinary differential equation models with discretization error quantification"
    SIAM/ASA Journal on Uncertainty Quantification, 9, 302–331, 2021.
  • 5. Matsuda, T.
    "Statistical analysis of kimariji in competitive karuta (in Japanese)"
    Japanese Journal of Applied Statistics, 49, 1--11, 2020.
  • 6. Matsuda, T. and Hyvarinen, A.
    "Estimation of non-normalized mixture models"
    22nd International Conference on Artificial Intelligence and Statistics (AISTATS 2019).
  • 7. Y. Maruyama, T. Matsuda and T. Onishi.
    "Harmonic Bayesian prediction under alpha-divergence"
    IEEE Transactions on Information Theory, 65, 5352--5366, 2019.
  • 9. Matsuda, T. and Komaki, F.
    "Time series decomposition into oscillation components and phase estimation"
    Neural Computation 29, 332--367, 2017.
  • 10. Matsuda, T. and Komaki, F.
    "Singular value shrinkage priors for Bayesian prediction"
    Biometrika 102, 843--854, 2015.

Related Links

Lab Members

Principal investigator

Takeru Matsuda
Unit Leader