Eric Laloy
Eric Laloy
Research scientist, Belgian Nuclear Research Centre (SCK-CEN)
Verified email at
Cited by
Cited by
High‐dimensional posterior exploration of hydrologic models using multiple‐try DREAM(ZS) and high‐performance computing
E Laloy, JA Vrugt
Water Resources Research 48 (1), 2012
Training‐image based geostatistical inversion using a spatial generative adversarial neural network
E Laloy, R Hérault, D Jacques, N Linde
Water Resources Research 54 (1), 381-406, 2018
Efficient posterior exploration of a high‐dimensional groundwater model from two‐stage Markov chain Monte Carlo simulation and polynomial chaos expansion
E Laloy, B Rogiers, JA Vrugt, D Mallants, D Jacques
Water Resources Research 49 (5), 2664-2682, 2013
HESS Opinions: Incubating deep-learning-powered hydrologic science advances as a community
C Shen, E Laloy, A Elshorbagy, A Albert, J Bales, FJ Chang, S Ganguly, ...
Hydrology and Earth System Sciences 22 (11), 5639-5656, 2018
Inversion using a new low-dimensional representation of complex binary geological media based on a deep neural network
E Laloy, R Hérault, J Lee, D Jacques, N Linde
Advances in water resources 110, 387-405, 2017
Effect of intercropping period management on runoff and erosion in a maize cropping system
E Laloy, CL Bielders
Journal of environmental quality 39 (3), 1001-1008, 2010
Parameter optimization and uncertainty analysis for plot-scale continuous modeling of runoff using a formal Bayesian approach
E Laloy, D Fasbender, CL Bielders
Journal of hydrology 380 (1-2), 82-93, 2010
Mass conservative three‐dimensional water tracer distribution from Markov chain Monte Carlo inversion of time‐lapse ground‐penetrating radar data
E Laloy, N Linde, JA Vrugt
Water Resources Research 48 (7), 2012
Probabilistic inference of multi‐G aussian fields from indirect hydrological data using circulant embedding and dimensionality reduction
E Laloy, N Linde, D Jacques, JA Vrugt
Water Resources Research 51 (6), 4224-4243, 2015
Electrical resistivity in a loamy soil: identification of the appropriate pedo-electrical model
E Laloy, M Javaux, M Vanclooster, C Roisin, CL Bielders
Vadose Zone Journal 10 (3), 1023-1033, 2011
Gradient-based deterministic inversion of geophysical data with generative adversarial networks: is it feasible?
E Laloy, N Linde, C Ruffino, R Hérault, G Gasso, D Jacques
Computers & Geosciences 133, 104333, 2019
Deep generative models in inversion: The impact of the generator's nonlinearity and development of a new approach based on a variational autoencoder
J Lopez-Alvis, E Laloy, F Nguyen, T Hermans
Computers & Geosciences 152, 104762, 2021
Broadening the use of machine learning in hydrology
C Shen, X Chen, E Laloy
Frontiers in Water 3, 681023, 2021
Effect of high-resolution spatial soil moisture variability on simulated runoff response using a distributed hydrologic model
J Minet, E Laloy, S Lambot, M Vanclooster
Hydrology and Earth System Sciences 15 (4), 1323-1338, 2011
How efficient are one-dimensional models to reproduce the hydrodynamic behavior of structured soils subjected to multi-step outflow experiments?
E Laloy, M Weynants, CL Bielders, M Vanclooster, M Javaux
Journal of hydrology 393 (1-2), 37-52, 2010
Plot scale continuous modelling of runoff in a maize cropping system with dynamic soil surface properties
E Laloy, CL Bielders
Journal of Hydrology 349 (3-4), 455-469, 2008
Merging parallel tempering with sequential geostatistical resampling for improved posterior exploration of high-dimensional subsurface categorical fields
E Laloy, N Linde, D Jacques, G Mariethoz
Advances in water resources 90, 57-69, 2016
Nested multiresolution hierarchical simulated annealing algorithm for porous media reconstruction
L Lemmens, B Rogiers, D Jacques, M Huysmans, R Swennen, JL Urai, ...
Physical Review E 100 (5), 053316, 2019
Bayesian full-waveform tomography with application to crosshole ground penetrating radar data
J Hunziker, E Laloy, N Linde
Geophysical Journal International 218 (2), 913-931, 2019
Emulation of CPU-demanding reactive transport models: a comparison of Gaussian processes, polynomial chaos expansion, and deep neural networks
E Laloy, D Jacques
Computational Geosciences 23, 1193-1215, 2019
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