144 citations · 294 across the 12 of their papers we have counts for
3 papers · 1 filter
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…
EikoNet: Solving the Eikonal equation with Deep Neural Networks
Jonathan D. Smith, Kamyar Azizzadenesheli, Zachary E. Ross
The recent deep learning revolution has created an enormous opportunity for accelerating compute capabilities in the context of physics-based simulations. Here, we propose EikoNet,…
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…