#### Children

Sign in to add traineeHaDi MaBouDi | grad student | IPM | |

Taro Toyoizumi | grad student | RIKEN BSI | |

Wakako Nakamura | post-doc | RIKEN | |

Masafumi Oizumi | post-doc | RIKEN | |

Si Wu | post-doc | Brain Science Institute, RIKEN | |

Masami Tatsuno | post-doc | 1999-2002 | RIKEN BSI |

Kosuke Hamaguchi | post-doc | 2004-2008 | RIKEN |

Keiji Miura | research scientist | ||

Shigeru Shinomoto | research scientist |

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#### Publications

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Ito S, Oizumi M, Amari S. (2020) Unified framework for the entropy production and the stochastic interaction based on information geometry Physical Review Research. 2 |

Amari SI, Karakida R, Oizumi M, et al. (2019) Information Geometry for Regularized Optimal Transport and Barycenters of Patterns. Neural Computation. 1-22 |

Amari S, Karakida R, Oizumi M. (2019) Statistical neurodynamics of deep networks: geometry of signal spaces Nonlinear Theory and Its Applications, Ieice. 10: 322-336 |

Yoshida Y, Karakida R, Okada M, et al. (2019) Statistical mechanical analysis of learning dynamics of two-layer perceptron with multiple output units Journal of Physics a: Mathematical and Theoretical. 52: 184002 |

Kass RE, Amari SI, Arai K, et al. (2018) Computational Neuroscience: Mathematical and Statistical Perspectives. Annual Review of Statistics and Its Application. 5: 183-214 |

Amari S, Karakida R, Oizumi M. (2018) Information geometry connecting Wasserstein distance and Kullback–Leibler divergence via the entropy-relaxed transportation problem Information Geometry. 1: 13-37 |

Amari SI, Ozeki T, Karakida R, et al. (2017) Dynamics of Learning in MLP: Natural Gradient and Singularity Revisited. Neural Computation. 1-33 |

Yoshida Y, Karakida R, Okada M, et al. (2017) Statistical Mechanical Analysis of Online Learning with Weight Normalization in Single Layer Perceptron Journal of the Physical Society of Japan. 86: 044002 |

Oizumi M, Tsuchiya N, Amari SI. (2016) Unified framework for information integration based on information geometry. Proceedings of the National Academy of Sciences of the United States of America |

Karakida R, Okada M, Amari SI. (2016) Dynamical analysis of contrastive divergence learning: Restricted Boltzmann machines with Gaussian visible units. Neural Networks : the Official Journal of the International Neural Network Society. 79: 78-87 |