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cs.LG2026
Active Learning for Conditional Generative Compressed Sensing
Alexander DeLise, Nick Dexter
Generative compressed sensing uses the range of a pretrained generator as a nonlinear model for recovering structured signals from limited measurements. We study a conditional vers…
cs.LG2025
Optimal Linear Baseline Models for Scientific Machine Learning
Alexander DeLise, Kyle Loh, Krish Patel +3
Across scientific domains, a fundamental challenge is to characterize and compute the mappings from underlying physical processes to observed signals and measurements. While nonlin…