Solving multiphysics-based inverse problems for geological carbon storag...
We present an iterative framework to improve the amortized approximation...
We present the Seismic Laboratory for Imaging and Modeling/Monitoring (S...
With the growing global deployment of carbon capture and sequestration
t...
Bayesian inference for high-dimensional inverse problems is challenged b...
Photoacoustic imaging (PAI) can image high-resolution structures of clin...
Fourier neural operators (FNOs) are a recently introduced neural network...
We present the SLIM (https://github.com/slimgroup) open-source software
...
Seismic monitoring of carbon storage sequestration is a challenging prob...
Seismic imaging is an ill-posed inverse problem that is challenged by no...
By building on recent advances in the use of randomized trace estimation...
We propose to use techniques from Bayesian inference and deep neural net...
Thanks to the combination of state-of-the-art accelerators and highly
op...
Time-lapse seismic monitoring of carbon storage and sequestration is oft...
Uncertainty quantification provides quantitative measures on the reliabi...
Inspired by recent work on extended image volumes that lays the ground f...
Obtaining samples from the posterior distribution of inverse problems wi...
In inverse problems, we often have access to data consisting of paired
s...
[Devito] is an open-source Python project based on domain-specific langu...
Uncertainty quantification for full-waveform inversion provides a
probab...
We present three imaging modalities that live on the crossroads of seism...
Achieving desirable receiver sampling in ocean bottom acquisition is oft...
In inverse problems, uncertainty quantification (UQ) deals with a
probab...
Uncertainty quantification is essential when dealing with ill-conditione...
This abstract presents a serverless approach to seismic imaging in the c...
Accurate forward modeling is important for solving inverse problems. An
...
We outline new approaches to incorporate ideas from convolutional networ...
Adapting the cloud for high-performance computing (HPC) is a challenging...
Many works on inverse problems in the imaging sciences consider
regulari...
We propose algorithms and software for computing projections onto the
in...
We introduce Devito, a new domain-specific language for implementing
hig...
Stencil computations are a key part of many high-performance computing
a...
Large scale parameter estimation problems are among some of the most
com...
Acquisition cost is a crucial bottleneck for seismic workflows, and low-...
Recent SVD-free matrix factorization formulations have enabled rank
mini...