389 citations · 1.5k across the 24 of their papers we have counts for
24 papers
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…
Dimensionality Reduction for Categorical Data
Debajyoti Bera, Rameshwar Pratap, Bhisham Dev Verma
Categorical attributes are those that can take a discrete set of values, e.g., colours. This work is about compressing vectors over categorical attributes to low-dimension discrete…
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…
Uncertainty Quantification and Experimental Design for Large-Scale Linear Inverse Problems under Gaussian Process Priors
Cédric Travelletti, David Ginsbourger, Niklas Linde
We consider the use of Gaussian process (GP) priors for solving inverse problems in a Bayesian framework. As is well known, the computational complexity of GPs scales cubically in…
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…