Jorge Lopez Alvis
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- Journal Article
- A1
- open access
Geophysical inversion uing a variational autoencoder to model an assembled spatial prior uncertainty
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- Conference Paper
- C1
- open access
Using a variational autoencoder and geologically-consistent transformations to model spatial prior information for geophysical inversion
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SBO project DISARM (S003719N) : deliverable 2.2A (Report freshwater discharge) and 2.2B (Methodology for combined used of onshore and marine ERT)
(2021) -
- Conference Paper
- C3
- open access
Imaging the subsurface to inform hydrological models : a geophysicist's perspective
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Deep generative models in inversion : the impact of the generator's nonlinearity and development of a new approach based on a variational autoencoder
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- PhD Thesis
- open access
Dimensionality reduction for geophysical inversion in highly structured subsurface environments
(2021) -
- Conference Paper
- C3
- open access
Estimation of spatially-structured subsurface parameters using variational autoencoders and gradient-based optimization
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- Conference Paper
- C3
- open access
Constraining gradient-based inversion with a variational autoencoder to reproduce geological patterns
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- Conference Paper
- C3
- open access
Efficient deterministic inversion of geophysical data constrained by deep generative models to estimate subsurface parameters with defined spatial patterns
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A cross-validation framework to extract data features for reducing structural uncertainty in subsurface heterogeneity