Compression Quality Prediction

Overview

We develop deep surrogate models that estimate the quality of scientific lossy compression and support informed configuration choices. QualityNet studies error-bounded compression quality prediction. DeepCQ extends this direction with a modular two-stage framework that reuses extracted features across compressors, quality metrics, and scientific datasets.

Publications