3-D Bayesian variational full waveform inversion
Seismic full-waveform inversion (FWI) provides high resolution images of the subsurface by
exploiting information in the recorded seismic waveforms. This is achieved by solving a …
exploiting information in the recorded seismic waveforms. This is achieved by solving a …
Bayesian seismic tomography using normalizing flows
We test a fully non-linear method to solve Bayesian seismic tomographic problems using
data consisting of observed traveltimes of first-arriving waves. Rather than using Monte …
data consisting of observed traveltimes of first-arriving waves. Rather than using Monte …
WISE: Full-waveform variational inference via subsurface extensions
We introduce a probabilistic technique for full-waveform inversion, using variational
inference and conditional normalizing flows to quantify uncertainty in migration-velocity …
inference and conditional normalizing flows to quantify uncertainty in migration-velocity …
Reliable amortized variational inference with physics-based latent distribution correction
Bayesian inference for high-dimensional inverse problems is computationally costly and
requires selecting a suitable prior distribution. Amortized variational inference addresses …
requires selecting a suitable prior distribution. Amortized variational inference addresses …
Understanding the Adjoint Method in Seismology: Theory and Implementation in the Time Domain
R Abreu - Surveys in Geophysics, 2024 - Springer
The adjoint method is a popular method used for seismic (full-waveform) inversion today.
The method is considered to give more realistic and detailed images of the interior of the …
The method is considered to give more realistic and detailed images of the interior of the …
Variational prior replacement in Bayesian inference and inversion
Many scientific investigations require that the values of a set of model parameters are
estimated using recorded data. In Bayesian inference, information from both observed data …
estimated using recorded data. In Bayesian inference, information from both observed data …
Fast Bayesian inversion of airborne electromagnetic data based on the invertible neural network
The inversion of airborne electromagnetic (AEM) data suffers from severe nonuniqueness in
the solution. Bayesian inference provides the means to estimate structural uncertainty with a …
the solution. Bayesian inference provides the means to estimate structural uncertainty with a …
WISER: multimodal variational inference for full-waveform inversion without dimensionality reduction
We develop a semiamortized variational inference (VI) framework designed for
computationally feasible uncertainty quantification in full-waveform inversion to explore the …
computationally feasible uncertainty quantification in full-waveform inversion to explore the …
Physically structured variational inference for Bayesian full waveform inversion
Full waveform inversion (FWI) creates high resolution models of the Earth's subsurface
structures from seismic waveform data. Due to the non‐linearity and non‐uniqueness of FWI …
structures from seismic waveform data. Due to the non‐linearity and non‐uniqueness of FWI …
Evaluation and comparison of spatial cluster detection methods for improved decision making of disease surveillance: a case study of national dengue surveillance in …
Background Dengue is a mosquito-borne disease that causes over 300 million infections
worldwide each year with no specific treatment available. Effective surveillance systems are …
worldwide each year with no specific treatment available. Effective surveillance systems are …