Shin-ichi Ito
Shin-ichi Ito
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Data assimilation for massive autonomous systems based on a second-order adjoint method
S Ito, H Nagao, A Yamanaka, Y Tsukada, T Koyama, M Kano, J Inoue
Physical Review E 94 (4), 043307, 2016
Data assimilation for phase-field models based on the ensemble Kalman filter
K Sasaki, A Yamanaka, S Ito, H Nagao
Computational Materials Science 141, 141-152, 2018
Grain growth prediction based on data assimilation by implementing 4DVar on multi-phase-field model
S Ito, H Nagao, T Kasuya, J Inoue
Science and Technology of Advanced Materials 18 (1), 857-868, 2017
Diffusion creep and grain growth in forsterite+ 20 vol% enstatite aggregates: 1. High‐resolution experiments and their data analyses
T Nakakoji, T Hiraga, H Nagao, S Ito, M Kano
Journal of Geophysical Research: Solid Earth 123 (11), 9486-9512, 2018
Seismic wavefield imaging based on the replica exchange Monte Carlo method
M Kano, H Nagao, D Ishikawa, S Ito, S Sakai, S Nakagawa, M Hori, ...
Geophysical Journal International 208 (1), 529-545, 2017
Dynamical scaling of fragment distribution in drying paste
S Ito, S Yukawa
Physical Review E 90 (4), 042909, 2014
Seismic wavefield imaging of long‐period ground motion in the Tokyo metropolitan area, Japan
M Kano, H Nagao, K Nagata, S Ito, S Sakai, S Nakagawa, M Hori, ...
Journal of Geophysical Research: Solid Earth 122 (7), 5435-5451, 2017
Seismic wavefield reconstruction based on compressed sensing using data-driven reduced-order model
T Nagata, K Nakai, K Yamada, Y Saito, T Nonomura, M Kano, S Ito, ...
Geophysical Journal International 233 (1), 33-50, 2023
Stochastic modeling on fragmentation process over lifetime and its dynamical scaling law of fragment distribution
S Ito, S Yukawa
Journal of the Physical Society of Japan 83 (12), 124005, 2014
Adjoint-based exact Hessian computation
S Ito, T Matsuda, Y Miyatake
BIT Numerical Mathematics 61 (2), 503-522, 2021
Recovering the past history of natural recording media by Bayesian inversion
T Kuwatani, H Nagao, S Ito, A Okamoto, K Yoshida, T Okudaira
Physical Review E 98 (4), 043311, 2018
Convolutional neural network to detect deep low-frequency tremors from seismic waveform images
R Kaneko, H Nagao, S Ito, K Obara, H Tsuruoka
Trends and Applications in Knowledge Discovery and Data Mining: PAKDD 2021 …, 2021
Observation site selection for physical model parameter estimation towards process-driven seismic wavefield reconstruction
K Nakai, T Nagata, K Yamada, Y Saito, T Nonomura, M Kano, S Ito, ...
Geophysical Journal International 234 (3), 1786-1805, 2023
Bayesian inference of grain growth prediction via multi-phase-field models
S Ito, H Nagao, T Kurokawa, T Kasuya, J Inoue
Physical Review Materials 3 (5), 053404, 2019
Detection of Deep Low‐Frequency Tremors From Continuous Paper Records at a Station in Southwest Japan About 50 Years Ago Based on Convolutional Neural Network
R Kaneko, H Nagao, S Ito, H Tsuruoka, K Obara
Journal of Geophysical Research: Solid Earth 128 (2), e2022JB024842, 2023
Adjoint-based uncertainty quantification for inhomogeneous friction on a slow-slipping fault
S Ito, M Kano, H Nagao
Geophysical Journal International 232 (1), 671-683, 2023
Forecasting temporal variation of aftershocks immediately after a main shock using Gaussian process regression
K Morikawa, H Nagao, S Ito, Y Terada, S Sakai, N Hirata
Geophysical Journal International 226 (2), 1018-1035, 2021
Phase prediction method for pattern formation in time-dependent Ginzburg-Landau dynamics for kinetic Ising model without a priori assumptions of domain patterns
R Anzaki, S Ito, H Nagao, M Mizumaki, M Okada, I Akai
Physical Review B 103 (9), 094408, 2021
時空間ブロッキングを用いたアジョイント法の高性能化――Forward と Backward の計算
池田朋哉, 伊藤伸一, 長尾大道, 片桐孝洋, 永井亨, 荻野正雄
情報処理学会論文誌コンピューティングシステム (ACS) 11 (1), 12-26, 2018
Optimizing Forward Computation in Adjoint Method via Multi-level Blocking
T Ikeda, S Ito, H Nagao, T Katagiri, T Nagai, M Ogino
Proceedings of the International Conference on High Performance Computing in …, 2018
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