16 citations · 25 across the 5 of their papers we have counts for
6 papers
Faster Uncertainty Quantification for Inverse Problems with Conditional Normalizing Flows
Ali Siahkoohi, Gabrio Rizzuti, Philipp A. Witte +1
In inverse problems, we often have access to data consisting of paired samples where are partial observations of a physical system, and represents…
Scaling through abstractions -- high-performance vectorial wave simulations for seismic inversion with Devito
Mathias Louboutin, Fabio Luporini, Philipp Witte +5
[Devito] is an open-source Python project based on domain-specific language and compiler technology. Driven by the requirements of rapid HPC applications development in exploration…
Parameterizing uncertainty by deep invertible networks, an application to reservoir characterization
Gabrio Rizzuti, Ali Siahkoohi, Philipp A. Witte +1
Uncertainty quantification for full-waveform inversion provides a probabilistic characterization of the ill-conditioning of the problem, comprising the sensitivity of the solution…
Time-domain sparsity promoting least-squares reverse time migration with source estimation
Mengmeng Yang, Zhilong Fang, Philipp Witte +1
Least-squares reverse time migration is well-known for its capability to generate artifact-free true-amplitude subsurface images through fitting observed data in the least-squares…
Serverless seismic imaging in the cloud
Philipp A. Witte, Mathias Louboutin, Charles Jones +1
This abstract presents a serverless approach to seismic imaging in the cloud based on high-throughput containerized batch processing, event-driven computations and a domain-specifi…
An Event-Driven Approach to Serverless Seismic Imaging in the Cloud
Philipp A. Witte, Mathias Louboutin, Henryk Modzelewski +3
Adapting the cloud for high-performance computing (HPC) is a challenging task, as software for HPC applications hinges on fast network connections and is sensitive to hardware fail…