Web: http://arxiv.org/abs/2201.08506

Jan. 24, 2022, 2:10 a.m. | He Sun, Katherine L. Bouman, Paul Tiede, Jason J. Wang, Sarah Blunt, Dimitri Mawet

cs.LG updates on arXiv.org arxiv.org

Inference is crucial in modern astronomical research, where hidden
astrophysical features and patterns are often estimated from indirect and noisy
measurements. Inferring the posterior of hidden features, conditioned on the
observed measurements, is essential for understanding the uncertainty of
results and downstream scientific interpretations. Traditional approaches for
posterior estimation include sampling-based methods and variational inference.
However, sampling-based methods are typically slow for high-dimensional inverse
problems, while variational inference often lacks estimation accuracy. In this
paper, we propose alpha-DPI, a deep …

arxiv deep uncertainty

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