Skip to content

Publications

Google Scholar Page

If you cannot find PDFs from your library, please send me a paper request on ResearchGate

2022

  • Zhu, W., Hou, A. B., Yang, R., Datta, A., Mousavi, S. M., Ellsworth, W. L., & Beroza, G. C. (2022). QuakeFlow: A Scalable Machine-learning-based Earthquake Monitoring Workflow with Cloud Computing. Geophysical Journal International.
  • Zhu, W., Tai, K. S., Mousavi, S. M., Bailis, P., & Beroza, G. C. (2022). An end-to-end earthquake detection method for joint phase picking and association using deep learning. Journal of Geophysical Research: Solid Earth.
  • Zhu, W., McBrearty, I. W., Mousavi, S. M., Ellsworth, W. L., & Beroza, G. C. (2022). Earthquake phase association using a bayesian gaussian mixture model. Journal of Geophysical Research: Solid Earth.
  • Xu, K., Zhu, W., & Darve, E. (2022). Learning generative neural networks with physics knowledge. Research in the Mathematical Sciences.
  • Yang, L., Liu, X., Zhu, W., Zhao, L., & Beroza, G. C. (2022). Toward improved urban earthquake monitoring through deep-learning-based noise suppression. Science advances.
  • Datta, A., Wu, D. J., Zhu, W., Cai, M., & Ellsworth, W. L. (2022). Deepshake: Shaking intensity prediction using deep spatiotemporal RNNs for earthquake early warning. Seismological Society of America.

2021

  • Zhu, W. (2021). Ph.D. Thesis: Applications of Deep Learning in Seismology. pdf
  • Zhu, W., Xu, K., Darve, E., & Beroza, G. C. (2021). A General Approach to Seismic Inversion with Automatic Differentiation. Computers & Geosciences.
  • Zhu, W., Xu, K., Darve, E., Biondi, B., & Beroza, G. C. (2021). Integrating deep neural networks with full-waveform inversion: Reparametrization, regularization, and uncertainty quantification. Geophysics.
  • Retailleau, L., Saurel, J.-M., Zhu, W., Satriano, C., Beroza, G. C., Issartel, S., ... Team, O. (2021). PhaseWorm: A real-time machine-learning-based algorithm for volcano-tectonic earthquake monitoring. Seismological Research Letters.
  • Tan, Y. J., Waldhauser, F., Ellsworth, W. L., Zhang, M., Zhu, W., Michele, M., ... Segou, M. (2021). Machine-learning-based high-resolution earthquake catalog reveals how complex fault structures were activated during the 2016–2017 central italy sequence. The Seismic Record.

2020

  • Zhu, W., Mousavi, S. M., & Beroza, G. C. (2020). Seismic Signal Augmentation to Improve Generalization of Deep Neural Networks. Advances in Geophysics. pdf
  • Zhu, W., Allison, K. L., Dunham, E. M., & Yang, Y. (2020). Fault Valving and Pore Pressure Evolution in Simulations of Earthquake Sequences and Aseismic Slip. Nature Communications.
  • Xu, K., Zhu, W., & Darve, E. (2020). Distributed machine learning for computational engineering using MPI. arXiv preprint.
  • Mousavi, S. M., Ellsworth, W. L., Zhu, W., Chuang, L. Y., & Beroza, G. C. (2020). Earthquake transformer—an attentive deep-learning model for simultaneous earthquake detection and phase picking. Nature Communications.
  • Chai, C., Maceira, M., Santos-Villalobos, H. J., Venkatakrishnan, S. V., Schoenball, M., Zhu, W., ... Team, E. C. (2020). Using a deep neural network and transfer learning to bridge scales for seismic phase picking. Geophysical Research Letters.
  • Liu, M., Zhang, M., Zhu, W., Ellsworth, W. L., & Li, H. (2020). Rapid characterization of the july 2019 Ridgecrest, california, earthquake sequence from raw seismic data using machine-learning phase picker. Geophysical Research Letters.
  • Park, Y., Mousavi, S. M., Zhu, W., Ellsworth, W. L., & Beroza, G. C. (2020). Machine-learning-based analysis of the Guy-Greenbrier, arkansas earthquakes: A tale of two sequences. Geophysical Research Letters.

2019

  • Zhu, W., Mousavi, S. M., & Beroza, G. C. (2019). Seismic Signal Denoising and Decomposition using Deep Neural Networks. IEEE Transactions on Geoscience and Remote Sensing.
  • Mousavi, S. M., Sheng, Y., Zhu, W., & Beroza, G. C. (2019). STanford EArthquake Dataset (STEAD): A global data set of seismic signals for AI. IEEE Access.
  • Mousavi, S. M., Zhu, W., Ellsworth, W., & Beroza, G. (2019). Unsupervised clustering of seismic signals using deep convolutional autoencoders. IEEE Geoscience and Remote Sensing Letters.
  • Mousavi, S. M., Zhu, W., Sheng, Y., & Beroza, G. C. (2019). CRED: A deep residual network of convolutional and recurrent units for earthquake signal detection. Scientific Reports.

2018

  • Zhu, W., & Beroza, G. C. (2018). PhaseNet: a deep-neural-network-based seismic arrival-time picking method. arXiv preprint.