Machine Learning for Distributed Acoustic Sensing data (MLDAS) v1.0.1
- Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
MLDAS is a Python-written package for exploratory data analysis and deep learning training on Distributed Acoustic Sensing data. The machine learning tools are powered by the PyTorch library and designed to work efficiently on large scale datasets using parallel computing. Various SLURM scripts as well as a tutorial have also been made available to allow geophysicists to quickly and easily implement the available tools in their analysis workflow on supercomputer facilities.
- Short Name / Acronym:
- Machine Learning for Distributed Acoustic Sensing data
- Site Accession Number:
- 2020-130
- Software Type:
- Scientific
- License(s):
- BSD 3-clause "New" or "Revised" License
- Research Organization:
- Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)
- Sponsoring Organization:
- USDOEPrimary Award/Contract Number:AC02-05CH11231
- DOE Contract Number:
- AC02-05CH11231
- Code ID:
- 51877
- OSTI ID:
- code-51877
- Country of Origin:
- United States
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