[S-CG55] Driving Solid Earth Science through Machine Learning

Sun. May 21, 2023 1:45 PM - 3:00 PM 302 (International Conference Hall, Makuhari Messe)

convener:Hisahiko Kubo(National Research Institute for Earth Science and Disaster Resilience), Yuki Kodera(Meteorological Research Institute, Japan Meteorological Agency), Makoto Naoi(Kyoto University), Keisuke Yano(The Institute of Statistical Mathematics), Chairperson:Ryoichiro Agata(Japan Agency for Marine-Earth Science and Technology), Keisuke Yano(The Institute of Statistical Mathematics)

Machine learning (ML) has brought innovations and remarkable results in various science fields including solid earth science. This session provides an opportunity to inspire each other for future developments by bringing studies of ML applications in various fields including solid earth science. We invite a wide range of presentations on ML and related research, from the budding to the more advanced.

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1:45 PM - 2:15 PM

[SCG55-07] Machine-learning-based waveform modeling: human voice case

★Invited Papers

*Shinnosuke Takamichi¹ (1.The University of Tokyo)

2:15 PM - 2:30 PM

[SCG55-08] Direct estimation of the fault slip of short-term slow slip events from GNSS data using deep learning

*Ryo Nakagawa¹, Yo Fukushima², Masayuki Kano¹, Keisuke Yano³, Kazuro Hirahara^4,5 (1.Graduate School of Science, Tohoku University, 2.International Research Institute of Disaster Science, Tohoku University, 3.Institute of Statistical Mathematics, 4.Riken, 5.Kagawa University)

2:30 PM - 2:45 PM

[SCG55-09] Physics Informed Deep Learning for Inverse Modeling of Coseismic Crustal Deformation

*Tomohisa Okazaki¹, Kazuro Hirahara¹, Naonori Ueda¹ (1.RIKEN Center for Advanced Intelligence Project)

2:45 PM - 3:00 PM

[SCG55-10] Bayesian first-arrival traveltime tomography using physics-informed neural networks and particle-based variational inference

*Ryoichiro Agata¹, Kazuya Shiraishi¹, Gou Fujie¹ (1.Japan Agency for Marine-Earth Science and Technology)

Session information