Philipp A. Witte

Orcid: 0000-0001-9142-0390

According to our database1, Philipp A. Witte authored at least 17 papers between 2018 and 2023.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Dataset
Other 

Links

On csauthors.net:

Bibliography

2023
Model-parallel Fourier neural operators as learned surrogates for large-scale parametric PDEs.
Comput. Geosci., September, 2023

InvertibleNetworks.jl: A Julia package for scalable normalizing flows.
CoRR, 2023

Learned multiphysics inversion with differentiable programming and machine learning.
CoRR, 2023

2022
SciAI4Industry - Solving PDEs for industry-scale problems with deep learning.
CoRR, 2022

Towards Large-Scale Learned Solvers for Parametric PDEs with Model-Parallel Fourier Neural Operators.
CoRR, 2022

Accelerating innovation with software abstractions for scalable computational geophysics.
CoRR, 2022

2021
Preconditioned training of normalizing flows for variational inference in inverse problems.
CoRR, 2021

2020
Software and Algorithms for Large-Scale Seismic Inverse Problems.
PhD thesis, 2020

Life is a scene and we are the actors: Assessing the usefulness of planning support theatres for smart city planning.
Comput. Environ. Urban Syst., 2020

An Event-Driven Approach to Serverless Seismic Imaging in the Cloud.
IEEE Trans. Parallel Distributed Syst., 2020

Architecture and Performance of Devito, a System for Automated Stencil Computation.
ACM Trans. Math. Softw., 2020

Faster Uncertainty Quantification for Inverse Problems with Conditional Normalizing Flows.
CoRR, 2020

Scaling through abstractions - high-performance vectorial wave simulations for seismic inversion with Devito.
CoRR, 2020

Parameterizing uncertainty by deep invertible networks, an application to reservoir characterization.
CoRR, 2020

Extended source imaging, a unifying framework for seismic & medical imaging.
CoRR, 2020

2019
Serverless seismic imaging in the cloud.
CoRR, 2019

2018
Devito: an embedded domain-specific language for finite differences and geophysical exploration.
CoRR, 2018


  Loading...