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 Conference Papers (Available on Advance Programs)  (Sort by: Date Descending)
 Results 1 - 7 of 7  /   
Committee Date Time Place Paper Title / Authors Abstract Paper #
EA, ASJ-H 2021-07-16
13:25		 Online 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) (Hokkaido) [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 (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 (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. (Kyoto) 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. (Kyoto) 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 (Tokyo) 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
 Results 1 - 7 of 7  /   
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