Poster session (Oct. 21st)

Special session » S21. Acceleration of seismological research through integration with information science

[S21P] PM-P

Mon. Oct 21, 2024 5:15 PM - 6:45 PM Room P (Main Hall (2F))

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[S21P-01] On regularity of physics-informed neural networks in solving ill-posed Cauchy problems

*Daisuke SATO¹, Tomohisa Okazaki² (1. Japan Agency for Marine-Earth Science and Technology, 2. Institute of Physical and Chemical Research)

[S21P-02] Hackathon on Large Language Models and Earthquake Researches

*Hisahiko KUBO¹, Stephen Wu², Masayuki Kano³, Shinya Katoh⁴, Atsuko Oana⁵, Tomohisa Okazaki⁶, Nozomi Okada⁷, Nobuki Kame⁴, Yuki Kodera⁸, Daisuke Sato⁹, Kengo Shimojo⁸, Koji Tamaribuchi¹⁰, Makoto Naoi¹¹, Ryuichi Nishiyama⁴, Kazuro Hirahara^6,12, Takashi Miyamoto¹³, Masumi Yamada¹⁴ (1. National Research Institute for Earth Science and Disaster Resilience, 2. The Institute of Statistical Mathematics, 3. Tohoku University, 4. Earthquake Research Institute, The University of Tokyo, 5. Institute of Technology, Shimizu Corporation, 6. Center for Advanced Intelligence Project, RIKEN, 7. Shizuoka University, 8. Meteorological Research Institute, 9. Japan Agency for Marine-Earth Science and Technology, 10. Japan Meteorological Agency, 11. Hokkaido University, 12. Kagawa University, 13. University of Yamanashi, 14. Disaster Prevention Research Institute, Kyoto University)

[S21P-03] Ateempt of detection of small earthquakes in Hakone volcano based on machine larning using multi-station data

*Ryo KURIHARA¹ (1. Hot Springs Research Institute of Kanagawa Prefecture)

[S21P-04] Parallel GPU Deep Learning Framework for Seismology and Application for Seismic Waveform from Nankai Trough

*Daisuke Sugiyama^1,2, Yojiro Yamamoto¹ (1. Japan Agency for Marine-Earth Science and Technology, 2. Kagoshima University)

[S21P-05] A Deep Learning Estimation of Tectonic Tremor Location from Single-Station Waveforms

*Amane Sugii¹, Yoshihiro Hiramatsu¹ (1. Kanazawa University)

[S21P-06] Detecting and locating tectonic tremors using deep learning: Application to Hi-net stations in the Nankai subduction zone

*Yuya Jinde¹, Amane Sugii¹, Yoshihiro Hiramatsu¹ (1. Kanazawa University)

[S21P-07] Development of deep-learning methods for seismic event detection in seafloor DAS data: creation of training/validation datasets

*GERARDO MANUEL MENDO¹, HIROMICHI NAGAO¹, SHINYA KATOH¹, MASANAO SHINOHARA² (1. Research Center for Computational Earth Science, Earthquake Research Institute, The University of Tokyo, 2. Research Center for Geophysical Observation and Instrumentation, Earthquake Research Institute, The University of Tokyo)

[S21P-08] Acquiring a Stochastic Differential Equation Representation to Characterize Tremors from Seismic Waveform Data Using Deep Learning

*Toshiro Kusui¹, Hiromichi Nagao¹, Shin-ichi Ito¹, Shinya Katoh¹, Tomoki Tokuda¹ (1. Univ. of Tokyo)

[S21P-09] Establishment and Result of Local Model through Transfer Learning of Deep Learning Detectors Using AN-net Data in Nagaoka Region

*Isao Kurosawa¹, Yuki kobayashi¹, Kodai Sagae², Takahiko Uchide² (1. INPEX CORPORATION, 2. Geological Survey of Japan. National Institute of Advanced Industrial Science and Technology)

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