Solid Earth Sciences (S)
Session Sub-categoryComplex & General (CG)
Session IDS-CG52
Title Driving Solid Earth Science through Machine Learning
Short Title Machine Learning in Solid Earth Sciences
Date & Time Oral session JUNE 3 (THU) AM1 Channel 18
Poster session JUNE 3 (THU) PM3
Main ConvenerName Hisahiko Kubo
Affiliation National Research Institute for Earth Science and Disaster Resilience
Co-Convener 1Name Yuki Kodera
Affiliation Meteorological Research Institute, Japan Meteorological Agency
Co-Convener 2Name Makoto Naoi
Affiliation Kyoto University
Co-Convener 3Name Keisuke Yano
Affiliation The Institute of Statistical Mathematics
Session Language J
Scope The development of machine learning techniques, such as deep learning, has led to innovations in various fields and is gaining ground in the solid earth sciences. This session provides an opportunity to inspire each other for future developments by bringing studies of machine learning applications in various fields including solid earth science. We especially welcome researches that have led to the discovery of phenomena and theories in solid earth science. We also look forward to studies on the black box problem of deep learning and efforts toward explainable AI.
Presentation Format Oral and Poster presentation
Collaboration Joint with -
Co-sponsored with -