144 citations · 201 across the 5 of their papers we have counts for
10 papers
Accelerating Time-Reversal Imaging with Neural Operators for Real-time Earthquake Locations
Hongyu Sun, Yan Yang, Kamyar Azizzadenesheli +2
Earthquake hypocenters form the basis for a wide array of seismological analyses. Pick-based earthquake location workflows rely on the accuracy of phase pickers and may be biased w…
Seismic wave propagation and inversion with Neural Operators
Yan Yang, Angela F. Gao, Jorge C. Castellanos +3
Seismic wave propagation forms the basis for most aspects of seismological research, yet solving the wave equation is a major computational burden that inhibits the progress of res…
Deep Learning-based Damage Mapping with InSAR Coherence Time Series
Oliver L. Stephenson, Tobias Köhne, Eric Zhan +4
Satellite remote sensing is playing an increasing role in the rapid mapping of damage after natural disasters. In particular, synthetic aperture radar (SAR) can image the Earth's s…
Data-driven Accelerogram Synthesis using Deep Generative Models
Manuel A. Florez, Michaelangelo Caporale, Pakpoom Buabthong +3
Robust estimation of ground motions generated by scenario earthquakes is critical for many engineering applications. We leverage recent advances in Generative Adversarial Networks…
Extracting dispersion curves from ambient noise correlations using deep learning
Xiaotian Zhang, Zhe Jia, Zachary E. Ross +1
We present a machine-learning approach to classifying the phases of surface wave dispersion curves. Standard FTAN analysis of surfaces observed on an array of receivers is converte…
Directivity Modes of Earthquake Populations with Unsupervised Learning
Zachary E. Ross, Daniel T. Trugman, Kamyar Azizzadenesheli +1
We present a novel approach for resolving modes of rupture directivity in large populations of earthquakes. A seismic spectral decomposition technique is used to first produce rela…