1 code implementation • 30 Oct 2022 • Rey Mendoza, Minh Nguyen, Judith Weng Zhu, Vincent Dumont, Talita Perciano, Juliane Mueller, Vidya Ganapati
However, obtaining high-quality object reconstructions for the training dataset requires high x-ray dose measurements that can destroy or alter the specimen before imaging is complete.
no code implementations • 12 Aug 2022 • Vincent Dumont, Xiangyang Ju, Juliane Mueller
We show that given proper hyperparameter tuning, we can find GANs that provide high-quality approximations of the desired quantities.
no code implementations • 12 Feb 2022 • Vincent Dumont, Trevor A. Bowen, Roger Roglans, Gregory Dobler, Mohit S. Sharma, Andy Karpf, Stuart D. Bale, Arne Wickenbrock, Elena Zhivun, Tom Kornack, Jonathan S. Wurtele, Dmitry Budker
We present a comparative analysis of urban magnetic fields between two American cities: Berkeley (California) and Brooklyn Borough of New York City (New York).
no code implementations • 4 Oct 2021 • Vincent Dumont, Casey Garner, Anuradha Trivedi, Chelsea Jones, Vidya Ganapati, Juliane Mueller, Talita Perciano, Mariam Kiran, Marc Day
We present a new software, HYPPO, that enables the automatic tuning of hyperparameters of various deep learning (DL) models.
no code implementations • 15 Oct 2020 • Vincent Dumont, Verónica Rodríguez Tribaldos, Jonathan Ajo-Franklin, Kesheng Wu
Deep Learning approaches for real, large, and complex scientific data sets can be very challenging to design.
no code implementations • 15 Oct 2020 • Vincent Dumont, Verónica Rodríguez Tribaldos, Jonathan Ajo-Franklin, Kesheng Wu
Moving loads such as cars and trains are very useful sources of seismic waves, which can be analyzed to retrieve information on the seismic velocity of subsurface materials using the techniques of ambient noise seismology.