Deep Symbolic Regression
- Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)
Symbolic regression is the task of finding tractable mathematical expressions that best fit an input dataset. Deep symbolic regression (DSR) searches the space of tractable mathematical expressions by using a recurrent neural network that generates mathematical expressions. The network is trained using reinforcement learning.
- Short Name / Acronym:
- DSR
- Project Type:
- Open Source, Publicly Available Repository
- Site Accession Number:
- 1009012
- Software Type:
- Scientific
- Version:
- 1.0
- License(s):
- BSD 3-clause "New" or "Revised" License
- Research Organization:
- Lawrence Livermore National Laboratory (LLNL), Livermore, CA (United States)
- Sponsoring Organization:
- USDOE National Nuclear Security Administration (NNSA)Primary Award/Contract Number:AC52-07NA27344
- DOE Contract Number:
- AC52-07NA27344
- Code ID:
- 34501
- OSTI ID:
- 1600741
- Country of Origin:
- United States
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