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 Conference Papers (Available on Advance Programs)  (Sort by: Date Descending)
 Results 1 - 8 of 8  /   
Committee Date Time Place Paper Title / Authors Abstract Paper #
EA, ASJ-H 2021-07-16
13:25
Online Online A feature selection method for a decision tree based audio event detection
Shin Murata, Shoichiro Saito, Kazunori Kobayashi (NTT) EA2021-18
 [more] EA2021-18
pp.83-88
IBISML 2018-11-05
15:10
Hokkaido Hokkaido Citizens Activites Center (Kaderu 2.7) [Poster Presentation] Normal mode selection of coherent phonons by Bayesian LARS-OLS
Itsushi Sakata, Yoshihiro Nagano (UTokyo), Yasushiko Igarashi (JST), Shin Murata (UTokyo), Kohji Mizoguchi (Osaka Prefecture Univ.), Ichiro Akai (Kumamoto Univ.), Masato Okada (UTokyo) IBISML2018-78
Coherent phonon (CP) signals contain normal modes representing the material property and experimental artifacts. It is p... [more] IBISML2018-78
pp.255-262
PRMU, IBISML, IPSJ-CVIM [detail] 2018-09-20
09:30
Fukuoka   Supervised anomaly detection using hyperspherical surface latent space autoencoder
Yuta Kawachi, Yuma Koizumi, Shin Murata, Noboru Harada (NTT) PRMU2018-36 IBISML2018-13
 [more] PRMU2018-36 IBISML2018-13
pp.1-8
IBISML 2017-11-10
13:00
Tokyo Univ. of Tokyo [Poster Presentation] Nonlinear parametric model based on power law for tsunami height prediction
Masashi Yoshikawa (UT), Yasuhiko Igarashi (JST), Shin Murata (UT), Toshitaka Baba (TU), Takane Hori (JAMSTEC), Masato Okada (UT) IBISML2017-70
When a subduction-zone earthquake occurs, we need to predict the tsunami height in order to cope with the tsunami damage... [more] IBISML2017-70
pp.261-267
IBISML 2016-11-17
14:00
Kyoto Kyoto Univ. Gaussian Markov random field model without periodic boundary conditions
Shun Katakami, Hirotaka Sakamoto, Shin Murata, Masato Okada (UTokyo) IBISML2016-83
In this study, we discuss Gaussian Markov random field model without periodic boundary conditions. First, we formulate a... [more] IBISML2016-83
pp.267-274
IBISML 2016-11-17
14:00
Kyoto Kyoto Univ. Extraction of low dimensional attractors embedded in a recurrent neural network by using Dynamic Mode Decomposition
Shin Murata (Univ. Tokyo), Masato Okada (Univ. Tokyo/RIKEN) IBISML2016-85
Dynamic Mode Decomposition (DMD) decomposes high-dimensional dynamical data into a few dynamic modes and has been develo... [more] IBISML2016-85
pp.279-285
NC, MBE 2015-03-17
13:00
Tokyo Tamagawa University Latent dynamics estimation from time-series spectral data
Shin Murata, Kenji Nagata (Univ. of Tokyo), Makoto Uemura (Hiroshima Univ.), Masato Okada (Univ. of Tokyo/RIKEN) MBE2014-173 NC2014-124
Estimation of latent dynamics from time-series data is important problem in a broad range of fields. In this research, w... [more] MBE2014-173 NC2014-124
pp.319-324
NC, MBE
(Joint)
2012-12-12
11:05
Aichi Toyohashi University of Technology Instabilities of spurious state with synaptic depression
Shin Murata, Yosuke Otsubo, Kenji Nagata (Univ. of Tokyo), Masato Okada (Univ. of Tokyo/BSI RIKEN) NC2012-79
The associative memory model is one of typical neural network model and has equilibrium state called spurious state in w... [more] NC2012-79
pp.31-36
 Results 1 - 8 of 8  /   
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