259 citations · 1.2k across the 51 of their papers we have counts for
3 papers · 1 filter
DLHub: Model and Data Serving for Science
Ryan Chard, Zhuozhao Li, Kyle Chard +7
While the Machine Learning (ML) landscape is evolving rapidly, there has been a relative lag in the development of the "learning systems" needed to enable broad adoption. Furthermo…
Measuring Swampiness: Quantifying Chaos in Large Heterogeneous Data Repositories
Luann Jung, Brendan Whitaker, Kyle Chard +1
As scientific data repositories and filesystems grow in size and complexity, they become increasingly disorganized. The coupling of massive quantities of data with poor organizatio…
Computing Environments for Reproducibility: Capturing the "Whole Tale"
Adam Brinckman, Kyle Chard, Niall Gaffney +11
The act of sharing scientific knowledge is rapidly evolving away from traditional articles and presentations to the delivery of executable objects that integrate the data and compu…