research
∙
07/18/2023
Solving multiphysics-based inverse problems with learned surrogates and constraints
Solving multiphysics-based inverse problems for geological carbon storag...
share
research
∙
05/15/2023
Refining Amortized Posterior Approximations using Gradient-Based Summary Statistics
We present an iterative framework to improve the amortized approximation...
research
∙
04/12/2023
Learned multiphysics inversion with differentiable programming and machine learning
We present the Seismic Laboratory for Imaging and Modeling/Monitoring (S...
research
∙
03/06/2023
Amortized Normalizing Flows for Transcranial Ultrasound with Uncertainty Quantification
We present a novel approach to transcranial ultrasound computed tomograp...
research
∙
12/16/2022
De-risking Carbon Capture and Sequestration with Explainable CO2 Leakage Detection in Time-lapse Seismic Monitoring Images
With the growing global deployment of carbon capture and sequestration t...
research
∙
04/24/2022
Memory Efficient Invertible Neural Networks for 3D Photoacoustic Imaging
Photoacoustic imaging (PAI) can image high-resolution structures of clin...
research
∙
04/04/2022
Towards Large-Scale Learned Solvers for Parametric PDEs with Model-Parallel Fourier Neural Operators
Fourier neural operators (FNOs) are a recently introduced neural network...
research
∙
03/28/2022
Accelerating innovation with software abstractions for scalable computational geophysics
We present the SLIM (https://github.com/slimgroup) open-source software ...
research
∙
03/27/2022
Learned coupled inversion for carbon sequestration monitoring and forecasting with Fourier neural operators
Seismic monitoring of carbon storage sequestration is a challenging prob...
research
∙
03/27/2022
Velocity continuation with Fourier neural operators for accelerated uncertainty quantification
Seismic imaging is an ill-posed inverse problem that is challenged by no...
research
∙
01/18/2022
Enabling wave-based inversion on GPUs with randomized trace estimation
By building on recent advances in the use of randomized trace estimation...
research
∙
06/13/2021
Low-memory stochastic backpropagation with multi-channel randomized trace estimation
Thanks to the combination of state-of-the-art accelerators and highly op...
research
∙
04/15/2021
Compressive time-lapse seismic monitoring of carbon storage and sequestration with the joint recovery model
Time-lapse seismic monitoring of carbon storage and sequestration is oft...
research
∙
04/01/2021
Ultra-low memory seismic inversion with randomized trace estimation
Inspired by recent work on extended image volumes that lays the ground f...
research
∙
01/11/2021
Preconditioned training of normalizing flows for variational inference in inverse problems
Obtaining samples from the posterior distribution of inverse problems wi...
research
∙
10/20/2020
Temporal blocking of finite-difference stencil operators with sparse "off-the-grid" sources
Stencil kernels dominate a range of scientific applications, including s...
research
∙
09/26/2020
Lossy Checkpoint Compression in Full Waveform Inversion
This paper proposes a new method that combines check-pointing methods wi...
research
∙
04/22/2020
Scaling through abstractions – high-performance vectorial wave simulations for seismic inversion with Devito
[Devito] is an open-source Python project based on domain-specific langu...
research
∙
04/15/2020
Extended source imaging, a unifying framework for seismic medical imaging
We present three imaging modalities that live on the crossroads of seism...
research
∙
11/27/2019
Serverless seismic imaging in the cloud
This abstract presents a serverless approach to seismic imaging in the c...
research
∙
09/27/2019
Neural network augmented wave-equation simulation
Accurate forward modeling is important for solving inverse problems. An ...
research
∙
09/03/2019
An Event-Driven Approach to Serverless Seismic Imaging in the Cloud
Adapting the cloud for high-performance computing (HPC) is a challenging...
research
∙
10/11/2018
Combining checkpointing and data compression for large scale seismic inversion
Seismic inversion and imaging are adjoint-based optimization problems th...
research
∙
08/06/2018
Devito: an embedded domain-specific language for finite differences and geophysical exploration
We introduce Devito, a new domain-specific language for implementing hig...
research
∙
07/09/2018
Architecture and performance of Devito, a system for automated stencil computation
Stencil computations are a key part of many high-performance computing a...
research
∙
01/12/2018
High-level python abstractions for optimal checkpointing in inversion problems
Inversion and PDE-constrained optimization problems often rely on solvin...
research
∙
07/12/2017
Optimised finite difference computation from symbolic equations
Domain-specific high-productivity environments are playing an increasing...
research
∙
09/12/2016
Devito: Towards a generic Finite Difference DSL using Symbolic Python
Domain specific languages (DSL) have been used in a variety of fields to...
research
∙
08/30/2016
Devito: automated fast finite difference computation
Domain specific languages have successfully been used in a variety of fi...
research
∙
08/13/2016