25 citations · 52 across the 5 of their papers we have counts for
5 papers
A Self-Supervised Approach to Reconstruction in Sparse X-Ray Computed Tomography
Rey Mendoza, Minh Nguyen, Judith Weng Zhu +4
Computed tomography has propelled scientific advances in fields from biology to materials science. This technology allows for the elucidation of 3-dimensional internal structure by…
Hyperparameter Optimization of Generative Adversarial Network Models for High-Energy Physics Simulations
Vincent Dumont, Xiangyang Ju, Juliane Mueller
The Generative Adversarial Network (GAN) is a powerful and flexible tool that can generate high-fidelity synthesized data by learning. It has seen many applications in simulating e…
HYPPO: A Surrogate-Based Multi-Level Parallelism Tool for Hyperparameter Optimization
Vincent Dumont, Casey Garner, Anuradha Trivedi +6
We present a new software, HYPPO, that enables the automatic tuning of hyperparameters of various deep learning (DL) models. Unlike other hyperparameter optimization (HPO) methods,…
Deep Learning on Real Geophysical Data: A Case Study for Distributed Acoustic Sensing Research
Vincent Dumont, Verónica Rodríguez Tribaldos, Jonathan Ajo-Franklin +1
Deep Learning approaches for real, large, and complex scientific data sets can be very challenging to design. In this work, we present a complete search for a finely-tuned and effi…
Deep Learning for Surface Wave Identification in Distributed Acoustic Sensing Data
Vincent Dumont, Verónica Rodríguez Tribaldos, Jonathan Ajo-Franklin +1
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 t…