| 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 | 55 | 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 | 31 | 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 | 25 | 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 | 17 | 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 | 16 | 2017 |
| Dynamical scaling of fragment distribution in drying paste S Ito, S Yukawa Physical Review E 90 (4), 042909, 2014 | 15 | 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 | 13 | 2017 |
| 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 | 10 | 2019 |
| 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 | 10 | 2014 |
| Adjoint-based exact Hessian computation S Ito, T Matsuda, Y Miyatake BIT Numerical Mathematics 61, 503-522, 2021 | 8 | 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 | 8 | 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 | 4 | 2021 |
| 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 | 2 | 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 | 2 | 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 | 2 | 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 | 2 | 2018 |
| Bayesian Modeling of the Equation of State for Liquid Iron in Earth's Outer Core T Matsumura, Y Kuwayama, K Ueki, T Kuwatani, Y Ando, K Nagata, S Ito, ... Journal of Geophysical Research: Solid Earth 126 (12), e2021JB023062, 2021 | | 2021 |
