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20222025
most citedDesign of experiments for the calibration of history-dependent models via deep reinforcement learning and an enhanced Kalman filter

2 citations · 8 across the 9 of their papers we have counts for

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stat.AP2024

Analysis and Optimization of Seismic Monitoring Networks with Bayesian Optimal Experiment Design

Jake Callahan, Kevin Monogue, Ruben Villarreal +1

Monitoring networks increasingly aim to assimilate data from a large number of diverse sensors covering many sensing modalities. Bayesian optimal experimental design (OED) seeks to…