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HypoNet Nankai PS: rapid hypocenter determination for the Nankai Trough using physics-informed neural networks with three-dimensional P- and S-wave velocity models
Ryoichiro Agata, Ayako Nakanishi, Dan Bassett +3
Rapid and accurate hypocenter determination based on three-dimensional (3D) seismic velocity models is essential for seismic monitoring in subduction zones, yet it remains computat…
Bayesian three-dimensional seismic travel-time tomography for active- and passive-source seismic data using physics-informed neural network
Ryoichiro Agata, Kazuya Shiraishi, Gou Fujie +1
Accurate 3D seismic velocity modeling through seismic travel-time tomography using both active- and passive-source data provides critical underpinning models for seismicity monitor…
Functional-prior-based approaches to Bayesian PDE-constrained inversion using physics-informed neural networks
Ryoichiro Agata, Tomohisa Okazaki
Physics-informed neural networks (PINNs) provide a mesh-free framework for solving PDE-constrained inverse problems, but their extension to Bayesian inversion still faces a fundame…