Continually Learning Neural-Operator Surrogate for Three-Dimensional Airborne Electromagnetic Bayesian Inversion
Geophysics
A continually learning neural-operator surrogate model replaces the traditional forward solver for efficient Bayesian inversion of three-dimensional time-domain airborne electromagnetic data, addressing prohibitive computational costs.
See LICENSE file Airborne EMBayesian InversionNeural Operator