Mathias Louboutin

research

∙ 07/18/2023

Solving multiphysics-based inverse problems with learned surrogates and constraints

Solving multiphysics-based inverse problems for geological carbon storag...

0 Ziyi Yin, et al. ∙

research

∙ 05/15/2023

Refining Amortized Posterior Approximations using Gradient-Based Summary Statistics

We present an iterative framework to improve the amortized approximation...

0 Rafael Orozco, et al. ∙

research

∙ 04/12/2023

Learned multiphysics inversion with differentiable programming and machine learning

We present the Seismic Laboratory for Imaging and Modeling/Monitoring (S...

0 Mathias Louboutin, et al. ∙

research

∙ 03/06/2023

Amortized Normalizing Flows for Transcranial Ultrasound with Uncertainty Quantification

We present a novel approach to transcranial ultrasound computed tomograp...

0 Rafael Orozco, et al. ∙

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...

0 Huseyin Tuna Erdinc, et al. ∙

research

∙ 04/24/2022

Memory Efficient Invertible Neural Networks for 3D Photoacoustic Imaging

Photoacoustic imaging (PAI) can image high-resolution structures of clin...

0 Rafael Orozco, et al. ∙

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...

0 Thomas J. Grady II, et al. ∙

research

∙ 03/28/2022

Accelerating innovation with software abstractions for scalable computational geophysics

We present the SLIM (https://github.com/slimgroup) open-source software ...

0 Mathias Louboutin, et al. ∙

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...

0 Ziyi Yin, et al. ∙

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...

0 Ali Siahkoohi, et al. ∙

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...

0 Mathias Louboutin, et al. ∙

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...

0 Mathias Louboutin, et al. ∙

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...

0 Ziyi Yin, et al. ∙

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...

0 Mathias Louboutin, et al. ∙

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...

8 Ali Siahkoohi, et al. ∙

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...

0 George Bisbas, et al. ∙

research

∙ 09/26/2020

Lossy Checkpoint Compression in Full Waveform Inversion

This paper proposes a new method that combines check-pointing methods wi...

0 Navjot Kukreja, et al. ∙

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...

0 Mathias Louboutin, et al. ∙

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...

0 Ziyi Yin, et al. ∙

research

∙ 11/27/2019

Serverless seismic imaging in the cloud

This abstract presents a serverless approach to seismic imaging in the c...

0 Philipp A. Witte, et al. ∙

research

∙ 09/27/2019

Neural network augmented wave-equation simulation

Accurate forward modeling is important for solving inverse problems. An ...

14 Ali Siahkoohi, et al. ∙

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...

0 Philipp A. Witte, et al. ∙

research

∙ 10/11/2018

Combining checkpointing and data compression for large scale seismic inversion

Seismic inversion and imaging are adjoint-based optimization problems th...

0 Navjot Kukreja, et al. ∙

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...

0 Mathias Louboutin, et al. ∙

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...

0 Fabio Luporini, et al. ∙

research

∙ 01/12/2018

High-level python abstractions for optimal checkpointing in inversion problems

Inversion and PDE-constrained optimization problems often rely on solvin...

0 Navjot Kukreja, et al. ∙

research

∙ 07/12/2017

Optimised finite difference computation from symbolic equations

Domain-specific high-productivity environments are playing an increasing...

0 Michael Lange, et al. ∙

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...

0 Michael Lange, et al. ∙

research

∙ 08/30/2016

Devito: automated fast finite difference computation

Domain specific languages have successfully been used in a variety of fi...

0 Navjot Kukreja, et al. ∙

research

∙ 08/13/2016

Performance prediction of finite-difference solvers for different computer architectures

The life-cycle of a partial differential equation (PDE) solver is often ...

0 Mathias Louboutin, et al. ∙

Mathias Louboutin

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