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Found 6 papers, 1 papers with code
A Self-Supervised Approach to Reconstruction in Sparse X-Ray Computed Tomography
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.
Hyperparameter Optimization of Generative Adversarial Network Models for High-Energy Physics Simulations
We show that given proper hyperparameter tuning, we can find GANs that provide high-quality approximations of the desired quantities.
Do cities have a unique magnetic pulse?
We present a comparative analysis of urban magnetic fields between two American cities: Berkeley (California) and Brooklyn Borough of New York City (New York).
HYPPO: A Surrogate-Based Multi-Level Parallelism Tool for Hyperparameter Optimization
We present a new software, HYPPO, that enables the automatic tuning of hyperparameters of various deep learning (DL) models.
Deep Learning on Real Geophysical Data: A Case Study for Distributed Acoustic Sensing Research
Deep Learning approaches for real, large, and complex scientific data sets can be very challenging to design.
Deep Learning for Surface Wave Identification in Distributed Acoustic Sensing Data
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.
