PANOM: Automatic Hyper-parameter Tuning for Inverse ProblemsDownload PDF

Published: 19 Oct 2021, Last Modified: 05 May 2023NeurIPS 2021 Deep Inverse Workshop PosterReaders: Everyone
Abstract: Automated hyper-parameter tuning for unsupervised learning, including inverse problems, remains a long-standing open problem due to the lack of validation data. In this work, we design an automatic tuning criterion for inverse problems and formulate it as a bilevel optimization task. We demonstrate the efficiency of our tuning scheme on various inverse problems and different test and out-of-distribution image samples at no expense of performance drops.
Conference Poster: pdf
1 Reply