E. Laloy

发表

Merging parallel tempering with sequential geostatistical resampling for improved posterior exploration of high-dimensional subsurface categorical fields

Gregoire Mariethoz, Eric Laloy, Diederik Jacques, 2016 .

Bayesian inversions of a dynamic vegetation model at four European grassland sites

Eric Laloy, Bernard Tychon, Julien Minet, 2015 .

Emulation of CPU-demanding reactive transport models: a comparison of Gaussian processes, polynomial chaos expansion, and deep neural networks

D. Jacques, E. Laloy, 2018, Computational Geosciences.

Inorganic carbon fluxes across the vadose zone of planted and unplanted soil mesocosms

Per Ambus, Claus E. Andersen, D. Jacques, 2014 .

Effect of high-resolution spatial soil moisture variability on simulated runoff response using a distributed hydrologic model

M. Vanclooster, J. Minet, S. Lambot, 2011 .

Effect of GPR-derived within-field soil moisture variability on the runoff response using a distributed hydrologic model

M. Vanclooster, J. Minet, S. Lambot, 2010 .

Mass conservative three‐dimensional water tracer distribution from Markov chain Monte Carlo inversion of time‐lapse ground‐penetrating radar data

Eric Laloy, Niklas Linde, Jasper A. Vrugt, 2012 .

High-resolution moisture profiles from full-waveform probabilistic inversion of TDR signals

J. Huisman, D. Jacques, E. Laloy, 2014 .

Mass conservative three-dimensional water tracer 1 distribution from MCMC inversion of time-lapse 2 GPR data

Eric Laloy, Niklas Linde, Jasper A. Vrugt, 2012 .

Inversion using a new low-dimensional representation of complex binary geological media based on a deep neural network

Eric Laloy, Diederik Jacques, Niklas Linde, 2017, 1710.09196.

Joint probabilistic inference of multi-Gaussian conductivity fields and their associated variograms from indirect hydrological data

J. Vrugt, N. Linde, D. Jacques, 2015 .

Electron spin resonance (ESR), optically stimulated luminescence (OSL) and terrestrial cosmogenic radionuclide (TCN) dating of quartz from a Plio-Pleistocene sandy formation in the Campine area, NE Belgium

V. Vanacker, E. Laloy, M. Christl, 2020 .

How efficient are one-dimensional models to reproduce the hydrodynamic behavior of structured soils subjected to multi-step outflow experiments?

Marnik Vanclooster, Mathieu Javaux, Eric Laloy, 2010 .

Scale-dependent parameterization of groundwater–surface water interactions in a regional hydrogeological model

J. Vanderborght, D. Jacques, E. Laloy, 2019, Journal of Hydrology.

Hydrogeological multiple-point statistics inversion by adaptive sequential Monte Carlo

N. Linde, E. Laloy, Macarena Amaya, 2022, Advances in Water Resources.

Improving Bayesian radiological profiling of waste drums using Dirichlet priors, Gaussian process priors, and hierarchical modeling

B. Rogiers, E. Laloy, A. Borella, 2022, 2205.07786.

HESS Opinions: Incubating deep-learning -powered science advances as a community

Daniel Kifer, F. Chang, A. Elshorbagy, 2018 .

Effect of intercropping period management on runoff and erosion in a maize cropping system.

C. Bielders, E. Laloy, 2010, Journal of environmental quality.

Improving Bayesian radiological profiling of waste drums using Dirichlet priors, Gaussian process priors, and hierarchical modeling

B. Rogiers, E. Laloy, A. Borella, 2022, 2205.07786.

Nested multiresolution hierarchical simulated annealing algorithm for porous media reconstruction.

M. Huysmans, R. Swennen, D. Jacques, 2019, Physical review. E.

Variational Bayesian inference with complex geostatistical priors using inverse autoregressive flows

N. Linde, E. Laloy, Shiran Levy, 2022, Comput. Geosci..

Efficient posterior exploration of a high‐dimensional groundwater model from two‐stage Markov chain Monte Carlo simulation and polynomial chaos expansion

D. Mallants, J. Vrugt, D. Jacques, 2013 .

Improving Bayesian radiological profiling of waste drums using Dirichlet priors, Gaussian process priors, and hierarchical modeling

B. Rogiers, E. Laloy, A. Borella, 2022, 2205.07786.

A combined data-driven, experimental and modelling approach for assessing the optimal composition of impregnation products for cementitious materials

J. Perko, I. Couckuyt, M. Mosquera, 2022, Cement and Concrete Composites.

Comparing Well and Geophysical Data for Temperature Monitoring Within a Bayesian Experimental Design Framework

E. Laloy, M. Ramgraber, T. Hermans, 2022, Water Resources Research.

Deep generative models in inversion: The impact of the generator's nonlinearity and development of a new approach based on a variational autoencoder

Eric Laloy, Frédéric Nguyen, Jorge Lopez-Alvis, 2021, Comput. Geosci..

Deep generative models in inversion: a review and development of a new approach based on a variational autoencoder

E. Laloy, F. Nguyen, T. Hermans, 2020, 2008.12056.

Towards a scientific-based assessment of long-term durability and performance of cementitious materials for radioactive waste conditioning and disposal

J. Perko, D. Jacques, B. Rogiers, 2021, Journal of Nuclear Materials.

A hybrid method for characterizing tillage-induced soil physical quality at the profile scale with fine spatial details

M. Vanclooster, C. Bielders, A. Alonso, 2022, Soil and Tillage Research.

Soil radioactivity-depth profiles from regularized inversion of borehole gamma spectrometry data.

J. Camps, M. Huysmans, B. Rogiers, 2021, Journal of environmental radioactivity.

Dilated Spatial Generative Adversarial Networks for Ergodic Image Generation pdf

Eric Laloy, Romain Hérault, Gilles Gasso, 2019, ArXiv.

Fluxes to Aquifers Beneath Cropland : Merging Measurements and Modeling

D. Jacques, E. Laloy, E. Thaysen, 2013 .

Parameterizing a Dynamic Architectural Model of the Root System of Spring Barley from Minirhizotron Data

Jan Vanderborght, Mathieu Javaux, Loïc Pagès, 2012 .

High‐dimensional posterior exploration of hydrologic models using multiple‐try DREAM(ZS) and high‐performance computing

Jasper A. Vrugt, Eric Laloy, J. Vrugt, 2012 .

HESS Opinions: Incubating deep-learning-powered hydrologic science advances as a community

Kuolin Hsu, Daniel Kifer, Zheng Fang, 2018, Hydrology and Earth System Sciences.

Bayesian inversion of a CRN depth profile to infer Quaternary erosion of the northwestern Campine Plateau (NE Belgium)

V. Vanacker, B. Rogiers, E. Laloy, 2017 .

Constraining Quaternary erosion of the Campine Plateau (NE Belgium) using Bayesian inversion of an in-situ produced 10 Be concentration depth profile

V. Vanacker, B. Rogiers, E. Laloy, 2016 .

Bayesian inference of root architectural model parameters from synthetic field data

Jan Vanderborght, Eric Laloy, Harry Vereecken, 2021, Plant and Soil.

Inference of multi-Gaussian relative permittivity fields by probabilistic inversion of crosshole ground-penetrating radar data

Eric Laloy, Niklas Linde, Jürg Hunziker, 2017 .

Probabilistic inference of multi‐Gaussian fields from indirect hydrological data using circulant embedding and dimensionality reduction

Eric Laloy, Diederik Jacques, Niklas Linde, 2015 .

Estimation of soil radioactivity-depth profiles using Bayesian inversion of borehole gamma spectrometry data.

J. Camps, M. Huysmans, B. Rogiers, 2022, Journal of environmental radioactivity.

Pixel-wise Conditioned Generative Adversarial Networks for Image Synthesis and Completion pdf

Eric Laloy, Gilles Gasso, Romain H'erault, 2020, Neurocomputing.

Training‐Image Based Geostatistical Inversion Using a Spatial Generative Adversarial Neural Network pdf

Eric Laloy, Romain Hérault, Diederik Jacques, 2017, ArXiv.

Plot scale continuous modelling of runoff in a maize cropping system with dynamic soil surface properties

C. Bielders, E. Laloy, 2008 .

Modelling intercrop management impact on runoff and erosion in a continuous maize cropping system: Part II. Model Pareto multi‐objective calibration and long‐term scenario analysis using disaggregated rainfall

Eric Laloy, Charles Bielders, C. Bielders, 2009 .

Gradient-based deterministic inversion of geophysical data with generative adversarial networks: Is it feasible?

Eric Laloy, Gilles Gasso, Romain H'erault, 2018, Comput. Geosci..

Editorial: Broadening the Use of Machine Learning in Hydrology

Chaopeng Shen, Xingyuan Chen, E. Laloy, 2021, Frontiers in Water.

A mesoscale framework for analysis of corrosion induced damage of concrete

A. Jivkov, E. Laloy, B. Kursten, 2019, Construction and Building Materials.

Parameter optimization and uncertainty analysis for plot-scale continuous modeling of runoff using a formal Bayesian approach.

Eric Laloy, Dominique Fasbender, Charles Bielders, 2010 .

Modelling intercrop management impact on runoff and erosion in a continuous maize cropping system: Part I. Model description, global sensitivity analysis and Bayesian estimation of parameter identifiability

C. Bielders, E. Laloy, 2009 .

2D inversion of in situ gamma-ray spectrometric measurements of 137Cs for site characterization.

J. Camps, M. Huysmans, B. Rogiers, 2022, Journal of environmental radioactivity.

Speeding Up Reactive Transport Simulations in Cement Systems by Surrogate Geochemical Modeling: Deep Neural Networks and k-Nearest Neighbors

D. Jacques, E. Laloy, 2021, Transport in Porous Media.

Approaching geoscientific inverse problems with vector-to-image domain transfer networks

N. Linde, D. Jacques, E. Laloy, 2020 .

Electrical Resistivity in a Loamy Soil: Identification of the Appropriate Pedo‐Electrical Model

Marnik Vanclooster, Mathieu Javaux, Eric Laloy, 2011 .

Bayesian full-waveform tomography with application to crosshole ground penetrating radar data

Eric Laloy, Niklas Linde, Jürg Hunziker, 2019, Geophysical Journal International.

Using deep generative neural networks to account for model errors in Markov chain Monte Carlo inversion

Eric Laloy, Niklas Linde, James Irving, 2021, Geophysical Journal International.

Effects of Lime and Concrete Waste on Vadose Zone Carbon Cycling

Per Ambus, Rasmus Jakobsen, D. Jacques, 2014 .

Bayesian inference of 1D activity profiles from segmented gamma scanning of a heterogeneous radioactive waste drum.

B. Rogiers, E. Laloy, A. Bielen, 2021, Applied radiation and isotopes : including data, instrumentation and methods for use in agriculture, industry and medicine.

A new framework for experimental design using Bayesian Evidential Learning: the case of wellhead protection area pdf

Eric Laloy, Thomas Hermans, Robin Thibaut, 2021, Journal of Hydrology.

Effects of Lime and Concrete Waste on Vadose Zone Carbon Cycling

P. Ambus, I. Jakobsen, E. Laloy, 2014 .

Adaptive sequential Monte Carlo for posterior inference and model selection among complex geological priors

N. Linde, E. Laloy, M. Amaya, 2021, Geophysical Journal International.

Effects of Lime and Concrete Waste on Vadose Zone Carbon Cycling

P. Ambus, I. Jakobsen, E. Laloy, 2014 .

Hydrogeological multiple-point statistics inversion by adaptive sequential Monte Carlo

N. Linde, E. Laloy, Macarena Amaya, 2022, Advances in Water Resources.

Inorganic carbon fluxes across the vadose zone of planted and unplanted soil mesocosms

P. Ambus, I. Jakobsen, E. Laloy, 2014 .

HESS Opinions: Deep learning as a promising avenue toward knowledge discovery in water sciences

Kuolin Hsu, Daniel Kifer, Zheng Fang, 2018 .