523 citations · 1.3k across the 8 of their papers we have counts for
9 papers
Spatiotemporal Analysis for Frequency-Magnitude Distribution of Earthquakes Across Mainland China: Comparing Classical and b-positive b-values Across Tectonic Regimes
Yuxin Zhou, Huai Zhang, S. Mostafa Mousavi
The Gutenberg-Richter power-law relationship essentially governs the frequency-magnitude distribution (FMD) of seismic activity. The b-value, as the slope of this distribution, is…
Automatic Knowledge Graph Construction and Query for Earthquake Catalogs
Yuxin Zhou, Huai Zhang, S. Mostafa Mousavi
In recent years, the number of events in earthquake catalogs has significantly increased due to the utilization of more effective deep learning based detectors and phase pickers bu…
Juxtaposition of Shallow Reservoir-Triggered Seismicity and Deep Tectonic Locking in the Qiaojia-Dongchuan Seismic Gap
Yuxin Zhou, Huai Zhang, S. Mostafa Mousavi +5
Identifying the critical state of mature seismic gaps is challenging, especially when anthropogenic stress perturbations, such as reservoir impoundment, superimpose on tectonic loa…
QuakeFlow: A Scalable Machine-learning-based Earthquake Monitoring Workflow with Cloud Computing
Weiqiang Zhu, Alvin Brian Hou, Robert Yang +4
Earthquake monitoring workflows are designed to detect earthquake signals and to determine source characteristics from continuous waveform data. Recent developments in deep learnin…
An End-to-End Earthquake Detection Method for Joint Phase Picking and Association using Deep Learning
Weiqiang Zhu, Kai Sheng Tai, S. Mostafa Mousavi +2
Earthquake monitoring by seismic networks typically involves a workflow consisting of phase detection/picking, association, and location tasks. In recent years, the accuracy of the…
Earthquake Phase Association using a Bayesian Gaussian Mixture Model
Weiqiang Zhu, Ian W. McBrearty, S. Mostafa Mousavi +2
Earthquake phase association algorithms aggregate picked seismic phases from a network of seismometers into individual earthquakes and play an important role in earthquake monitori…
Bayesian-Deep-Learning Estimation of Earthquake Location from Single-Station Observations
S. Mostafa Mousavi, Gregory C. Beroza
We present a deep learning method for single-station earthquake location, which we approach as a regression problem using two separate Bayesian neural networks. We use a multi-task…
A Machine-Learning Approach for Earthquake Magnitude Estimation
S. Mostafa Mousavi, Gregory C. Beroza
In this study we develop a single-station deep-learning approach for fast and reliable estimation of earthquake magnitude directly from raw waveforms. We design a regressor compose…
Seismic Signal Denoising and Decomposition Using Deep Neural Networks
Weiqiang Zhu, S. Mostafa Mousavi, Gregory C. Beroza
Denoising and filtering are widely used in routine seismic-data-processing to improve the signal-to-noise ratio (SNR) of recorded signals and by doing so to improve subsequent anal…