We use artificial neural networks (ANNs) based on the Boltzmann machine (BM)
architectures as an encoder of ab initio molecular many-electron wave functions …

Artificial neural networks (ANNs) for material modeling have received significant interest. We
recently reported an adaptation of ANNs based on Boltzmann machine (BM) architectures to …

We present a novel blind source separation (BSS) method, called information geometric
blind source separation (IGBSS). Our formulation is based on the log-linear model equipped …

We present the Additive Poisson Process (APP), a novel framework that can model the
higher-order interaction effects of the intensity functions in stochastic processes using lower …

In this study, we address a learning problem of probabilistic models that represent high-
order interactions among discrete attributes. To include the second-order interaction of …

We show that generalized additive models (GAMs) can be treated via the log-linear model
on a structured sample space, which has a well established information geometric …

Machine learning models increase their representational power by increasing the number of
parameters in the model. The number of parameters in the model can be increased by …

We present the Additive Poisson Process (APP), a novel framework that can model the
higher-order interaction effects of the intensity functions in Poisson processes using …

With the continuing surge in digitalization within the travel industry and the increased
demand of personalized services, understanding customer behaviour is becoming a …

ここで,[N]={1, 2,..., N} であり, x1,..., xN は入力として与えられたデータである. 最尤推定によって
パラメータ b と w を学習した後は, ボルツマンマシンを生成モデルとして利用できる …