389 citations · 1.5k across the 24 of their papers we have counts for
19 papers · 1 filter
Bayesian tomography using polynomial chaos expansion and deep generative networks
Giovanni Angelo Meles, Macarena Amaya, Shiran Levy +2
Implementations of Markov chain Monte Carlo (MCMC) methods need to confront two fundamental challenges: accurate representation of prior information and efficient evaluation of lik…
Bayesian tomography with prior-knowledge-based parametrization and surrogate modeling
Giovanni Angelo Meles, Niklas Linde, Stefano Marelli
We present a Bayesian tomography framework operating with prior-knowledge-based parametrization that is accelerated by surrogate models. Standard high-fidelity forward solvers solv…
Lithological Tomography with the Correlated Pseudo-Marginal Method
Lea Friedli, Niklas Linde, David Ginsbourger +1
We consider lithological tomography in which the posterior distribution of (hydro)geological parameters of interest is inferred from geophysical data by treating the intermediate g…
Adaptive sequential Monte Carlo for posterior inference and model selection among complex geological priors
M. Amaya, N. Linde, E. Laloy
Bayesian model selection enables comparison and ranking of conceptual subsurface models described by spatial prior models, according to the support provided by available geophysica…
Advancing quantitative understanding of self-potential signatures in the critical zone through long-term monitoring
Kaiyan Hu, Damien Jougnot, Qinghua Huang +2
The self-potential (SP) method is a passive geophysical technique, which may offer insights about water and ionic fluxes in the vadose zone. The main obstacles presently prohibitin…
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…