105 citations · 133 across the 16 of their papers we have counts for
4 papers · 1 filter
Exploring Lossy Compressibility through Statistical Correlations of Scientific Datasets
David Krasowska, Julie Bessac, Robert Underwood +3
Lossy compression plays a growing role in scientific simulations where the cost of storing their output data can span terabytes. Using error bounded lossy compression reduces the a…
Nonstationary seasonal model for daily mean temperature distribution bridging bulk and tails
Mitchell Krock, Julie Bessac, Michael L. Stein +1
In traditional extreme value analysis, the bulk of the data is ignored, and only the tails of the distribution are used for inference. Extreme observations are specified as values…
Neural Networks for Parameter Estimation in Intractable Models
Amanda Lenzi, Julie Bessac, Johann Rudi +1
We propose to use deep learning to estimate parameters in statistical models when standard likelihood estimation methods are computationally infeasible. We show how to estimate par…
SDRBench: Scientific Data Reduction Benchmark for Lossy Compressors
Kai Zhao, Sheng Di, Xin Liang +5
Efficient error-controlled lossy compressors are becoming critical to the success of today's large-scale scientific applications because of the ever-increasing volume of data produ…