Zobrazeno 1 - 10
of 64
pro vyhledávání: '"Mototake, Yoh-ichi"'
Autor:
Nagata, Kenji, Mototake, Yoh-ichi
The Metropolis algorithm is one of the Markov chain Monte Carlo (MCMC) methods that realize sampling from the target probability distribution. In this paper, we are concerned with the sampling from the distribution in non-identifiable cases that invo
Externí odkaz:
http://arxiv.org/abs/2406.00369
This study delves into the domain of dynamical systems, specifically the forecasting of dynamical time series defined through an evolution function. Traditional approaches in this area predict the future behavior of dynamical systems by inferring the
Externí odkaz:
http://arxiv.org/abs/2306.16593
Autor:
Kumazoe, Hiroyuki, Iwamitsu, Kazunori, Imamura, Masaki, Takahashi, Kazutoshi, Mototake, Yoh-ichi, Okada, Masato, Akai, Ichiro
We analyzed the X-ray photoemission spectra (XPS) of carbon 1s states in graphene and oxygen-intercalated graphene grown on SiC(0001) using Bayesian spectroscopy. To realize highly accurate spectral decomposition of the XPS spectra, we proposed a fra
Externí odkaz:
http://arxiv.org/abs/2306.03575
Autor:
Mototake, Yoh-ichi, Taguchi, Y-h.
When there are signals and noises, physicists try to identify signals by modeling them, whereas statisticians oppositely try to model noise to identify signals. In this study, we applied the statisticians' concept of signal detection of physics data
Externí odkaz:
http://arxiv.org/abs/2304.06522
Fracture surfaces provide various types of information about fracture. The fracture toughness $K_{{\rm I}c}$, which represents the resistance to fracture, can be estimated using the three-dimensional (3D) information of a fracture surface, i.e., its
Externí odkaz:
http://arxiv.org/abs/2204.13912
Topological data analysis (TDA) is a versatile tool that can be used to extract scientific knowledge from complex pattern formation processes. However, the physics correspondence between the features obtained from TDA and pattern dynamics does not ag
Externí odkaz:
http://arxiv.org/abs/2204.12194
Autor:
Mototake, Yoh-ichi
Publikováno v:
Phys. Rev. E 103, 033303 (2021)
Understanding complex systems with their reduced model is one of the central roles in scientific activities. Although physics has greatly been developed with the physical insights of physicists, it is sometimes challenging to build a reduced model of
Externí odkaz:
http://arxiv.org/abs/2001.00111
We theoretically study the landscape of the training error for neural networks in overparameterized cases. We consider three basic methods for embedding a network into a wider one with more hidden units, and discuss whether a minimum point of the nar
Externí odkaz:
http://arxiv.org/abs/1906.04868
In this paper, we propose a new method of Bayesian measurement for spectral deconvolution, which regresses spectral data into the sum of unimodal basis function such as Gaussian or Lorentzian functions. Bayesian measurement is a framework for conside
Externí odkaz:
http://arxiv.org/abs/1812.05501
Autor:
Niizato, Takayuki, Sakamoto, Kotaro, Mototake, Yoh-ichi, Tomaru, Takenori, Hoshika, Tomotaro, Fukushima, Toshiki
Collective behaviour is known to be the result of diverse dynamics and is sometimes likened to a living system. Although many studies have revealed the dynamics of various collective behaviours, their main focus was on the information process inside
Externí odkaz:
http://arxiv.org/abs/1812.00718