no code implementations • 30 Jun 2021 • Sankalp Gilda, Stark C. Draper, Sebastien Fabbro, William Mahoney, Simon Prunet, Kanoa Withington, Matthew Wilson, Yuan-Sen Ting, Andrew Sheinis
We leverage epistemic and aleatoric uncertainties in conjunction with probabilistic generative modeling to identify candidate vent adjustments that are in-distribution (ID); for the optimal configuration for each ID sample, we predict the reduction in required observing time to achieve a fixed SNR.