Zobrazeno 1 - 10
of 95
pro vyhledávání: '"Louboutin, Mathias"'
Due to their uncertainty quantification, Bayesian solutions to inverse problems are the framework of choice in applications that are risk averse. These benefits come at the cost of computations that are in general, intractable. New advances in machin
Externí odkaz:
http://arxiv.org/abs/2405.05398
Time-lapse seismic monitoring necessitates integrated workflows that combine seismic and reservoir modeling to enhance reservoir property estimation. We present a feasibility study of an end-to-end inversion framework that directly inverts for permea
Externí odkaz:
http://arxiv.org/abs/2403.04083
Autor:
Orozco, Rafael, Witte, Philipp, Louboutin, Mathias, Siahkoohi, Ali, Rizzuti, Gabrio, Peters, Bas, Herrmann, Felix J.
InvertibleNetworks.jl is a Julia package designed for the scalable implementation of normalizing flows, a method for density estimation and sampling in high-dimensional distributions. This package excels in memory efficiency by leveraging the inheren
Externí odkaz:
http://arxiv.org/abs/2312.13480
Autor:
Bisbas, George, Nelson, Rhodri, Louboutin, Mathias, Kelly, Paul H. J., Luporini, Fabio, Gorman, Gerard
Partial differential equations (PDEs) are crucial in modelling diverse phenomena across scientific disciplines, including seismic and medical imaging, computational fluid dynamics, image processing, and neural networks. Solving these PDEs on a large
Externí odkaz:
http://arxiv.org/abs/2312.13094
We introduce a probabilistic technique for full-waveform inversion, employing variational inference and conditional normalizing flows to quantify uncertainty in migration-velocity models and its impact on imaging. Our approach integrates generative a
Externí odkaz:
http://arxiv.org/abs/2401.06230
Autor:
Zhang, Yijun, Yin, Ziyi, López, Oscar, Siahkoohi, Ali, Louboutin, Mathias, Herrmann, Felix J.
The massive cost of 3D acquisition calls for methods to reduce the number of receivers by designing optimal receiver sampling masks. Recent studies on 2D seismic showed that maximizing the spectral gap of the subsampling mask leads to better wavefiel
Externí odkaz:
http://arxiv.org/abs/2311.02298
Solving multiphysics-based inverse problems for geological carbon storage monitoring can be challenging when multimodal time-lapse data are expensive to collect and costly to simulate numerically. We overcome these challenges by combining computation
Externí odkaz:
http://arxiv.org/abs/2307.11099
We present an iterative framework to improve the amortized approximations of posterior distributions in the context of Bayesian inverse problems, which is inspired by loop-unrolled gradient descent methods and is theoretically grounded in maximally i
Externí odkaz:
http://arxiv.org/abs/2305.08733
Autor:
Louboutin, Mathias, Yin, Ziyi, Orozco, Rafael, Grady II, Thomas J., Siahkoohi, Ali, Rizzuti, Gabrio, Witte, Philipp A., Møyner, Olav, Gorman, Gerard J., Herrmann, Felix J.
We present the Seismic Laboratory for Imaging and Modeling/Monitoring (SLIM) open-source software framework for computational geophysics and, more generally, inverse problems involving the wave-equation (e.g., seismic and medical ultrasound), regular
Externí odkaz:
http://arxiv.org/abs/2304.05592
Autor:
Orozco, Rafael, Louboutin, Mathias, Siahkoohi, Ali, Rizzuti, Gabrio, van Leeuwen, Tristan, Herrmann, Felix
We present a novel approach to transcranial ultrasound computed tomography that utilizes normalizing flows to improve the speed of imaging and provide Bayesian uncertainty quantification. Our method combines physics-informed methods and data-driven m
Externí odkaz:
http://arxiv.org/abs/2303.03478