1 citations · 1 across the 3 of their papers we have counts for
4 papers
Prediction of spatio-temporal data on meshed surfaces using advection-diffusion SPDEs
Mike Pereira, Lucia Clarotto, Nicolas Desassis
The aim of this work is to propose a statistical model for spatio-temporal data on meshed surfaces based on the Stochastic Partial Differential Equation (SPDE) modeling approach. S…
Diffusion prior as a direct regularization term for FWI
Yuke Xie, Hervé Chauris, Nicolas Desassis
Diffusion models have recently shown promise as powerful generative priors for inverse problems. However, conventional applications require solving the full reverse diffusion proce…
Stochastic full waveform inversion with deep generative prior for uncertainty quantification
Yuke Xie, Hervé Chauris, Nicolas Desassis
To obtain high-resolution images of subsurface structures from seismic data, seismic imaging techniques such as Full Waveform Inversion (FWI) serve as crucial tools. However, FWI i…
Neural variational Data Assimilation with Uncertainty Quantification using SPDE priors
Maxime Beauchamp, Ronan Fablet, Simon Benaichouche +3
The spatio-temporal interpolation of large geophysical datasets has historically been addressed by Optimal Interpolation (OI) and more sophisticated equation-based or data-driven D…