Efficient training-image based geostatistical simulation and inversion using a spatial generative adversarial neural network. - Eric Laloy; Romain Hérault; Diederik Jacques; Niklas Linde (CoRR, 2017)

Pixel-wise Conditioning of Generative Adversarial Networks. - Cyprien Ruffino; Romain Hérault; Eric Laloy; Gilles Gasso (ESANN, 2019)

Dilated Spatial Generative Adversarial Networks for Ergodic Image Generation. - Cyprien Ruffino; Romain Hérault; Eric Laloy; Gilles Gasso (CoRR, 2019)

Gradient-based deterministic inversion of geophysical data with generative adversarial networks: Is it feasible? - Eric Laloy; Niklas Linde; Cyprien Ruffino; Romain Hérault; Gilles Gasso; Diederik Jacques (Comput. Geosci., 2019)

Pixel-wise conditioned generative adversarial networks for image synthesis and completion. - Cyprien Ruffino; Romain Hérault; Eric Laloy; Gilles Gasso (Neurocomputing, 2020)

A new framework for experimental design using Bayesian Evidential Learning: the case of wellhead protection area. - Robin Thibaut; Eric Laloy; Thomas Hermans (CoRR, 2021)

Deep generative models in inversion: The impact of the generator's nonlinearity and development of a new approach based on a variational autoencoder. - Jorge Lopez-Alvis; Eric Laloy; Frédéric Nguyen; Thomas Hermans (Comput. Geosci., 2021)

Variational Bayesian inference with complex geostatistical priors using inverse autoregressive flows. - Shiran Levy; Eric Laloy; Niklas Linde (Comput. Geosci., 2023)

Deep learning surrogate for predicting hydraulic conductivity tensors from stochastic discrete fracture-matrix models. - Martin Spetlík; Jan Brezina; Eric Laloy (CoRR, 2024)