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physics.geo-ph2019
Approaching geoscientific inverse problems with vector-to-image domain transfer networks
Eric Laloy, Niklas Linde, Diederik Jacques
We present vec2pix, a deep neural network designed to predict categorical or continuous 2D subsurface property fields from one-dimensional measurement data (e.g., time series), the…
physics.geo-ph2018
Gradient-based deterministic inversion of geophysical data with Generative Adversarial Networks: is it feasible?
Eric Laloy, Niklas Linde, Cyprien Ruffino +3
Global probabilistic inversion within the latent space learned by a Generative Adversarial Network (GAN) has been recently demonstrated. Compared to inversion on the original model…