2 citations · 3 across the 3 of their papers we have counts for
3 papers
Workflows Community Summit: Bringing the Scientific Workflows Community Together
Rafael Ferreira da Silva, Henri Casanova, Kyle Chard +42
Scientific workflows have been used almost universally across scientific domains, and have underpinned some of the most significant discoveries of the past several decades. Many of…
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…