42 citations · 45 across the 4 of their papers we have counts for
4 papers
Parallelizing Training of Deep Generative Models on Massive Scientific Datasets
Sam Ade Jacobs, Brian Van Essen, David Hysom +11
Training deep neural networks on large scientific data is a challenging task that requires enormous compute power, especially if no pre-trained models exist to initialize the proce…
Scalable Topological Data Analysis and Visualization for Evaluating Data-Driven Models in Scientific Applications
Shusen Liu, Di Wang, Dan Maljovec +13
With the rapid adoption of machine learning techniques for large-scale applications in science and engineering comes the convergence of two grand challenges in visualization. First…
Equation of state of warm-dense boron nitride combining computation, modeling, and experiment
Shuai Zhang, Amy Lazicki, Burkhard Militzer +18
The equation of state (EOS) of materials at warm dense conditions poses significant challenges to both theory and experiment. We report a combined computational, modeling, and expe…
Bayesian Analysis of Inertial Confinement Fusion Experiments at the National Ignition Facility
J. A. Gaffney, D. Clark, V. Sonnad +1
We develop a Bayesian inference method that allows the efficient determination of several interesting parameters from complicated high-energy-density experiments performed on the N…