Modeling Time Series Data with Ordinary Differential Equations and Neural Networks
- Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)
- UC Merced
This suite of code learns neural network models to emulate the dynamics of time series data. To do so, it learns a set of "neural shape functions" that provide a common vocabulary for expressing the various dynamics operators. The code is implemented in Python and TensorFlow.
- Short Name / Acronym:
- PSINN
- Site Accession Number:
- 989386
- Software Type:
- Scientific
- License(s):
- MIT License
- Programming Language(s):
- Python
- 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:
- 31120
- OSTI ID:
- code-31120
- Country of Origin:
- United States
Similar Records
Archparse
NEURAL NETWORK FOR COHERENT DIFFRACTION IMAGE INVERSION
PyTorch Implementation of Log-Additive Convolutional Neural Networks
Software
·
Wed Jul 14 20:00:00 EDT 2021
·
OSTI ID:code-66986
NEURAL NETWORK FOR COHERENT DIFFRACTION IMAGE INVERSION
Software
·
Thu Apr 29 20:00:00 EDT 2021
·
OSTI ID:code-62502
PyTorch Implementation of Log-Additive Convolutional Neural Networks
Software
·
Wed May 15 20:00:00 EDT 2024
·
OSTI ID:code-140120