Published 2024
| Version v2
Dataset
Open
WaveBench: Benchmark Datasets for Linear Wave Propagation PDEs
Creators
- 1. University of Basel
- 2. Rice University
- 3. Team Makutu – Inria Bordeaux, University of Pau et des Pays de l'Adour
Description
Wave-based imaging techniques play a critical role in diverse scientific, medical, and industrial endeavors, from discovering hidden structures beneath the Earth's surface to ultrasound diagnostics. They rely on accurate solutions to the forward and inverse problems for partial differential equations (PDEs) that govern wave propagation. Surrogate PDE solvers based on machine learning emerged as an effective approach to computing the solutions more efficiently than via classical numerical schemes. Our dataset, WaveBench, is a collection of benchmark datasets for wave propagation PDEs. Our code is available at https://github.com/wavebench/wavebench/.
Files
wavebench_dataset.zip
Files
(147.7 GB)
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md5:b9ba32429e7367b85bf74d2a8cfd2f40
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Additional details
Funding
Dates
- Accepted
-
2024