NREL / phygnn
physics-guided neural networks (phygnn)
☆91Updated this week
Alternatives and similar repositories for phygnn:
Users that are interested in phygnn are comparing it to the libraries listed below
- ☆89Updated 5 years ago
- ☆176Updated 2 weeks ago
- Physics-guided Neural Networks (PGNN) : An Application In Lake Temperature Modelling☆107Updated 3 years ago
- ☆116Updated 5 years ago
- ☆124Updated 2 years ago
- ☆86Updated 2 years ago
- Physics informed neural networks for control-oriented building thermal models☆27Updated 3 years ago
- Physics-informed neural networks package☆300Updated 2 years ago
- A python implementation of Physics-informed Spline Learning for nonlinear dynamics discovery.☆25Updated 3 years ago
- An interpretable data-driven framework for building generative reduced order models with embedded uncertainty quantification☆32Updated last month
- Physics-informed learning of governing equations from scarce data☆140Updated last year
- Physics-Constrained Bayesian Neural Network for Fluid Flow Reconstruction with Sparse and Noisy Data☆48Updated 4 years ago
- PySensors is a Python package for sparse sensor placement☆88Updated this week
- multifidelity global sensitivity analysis☆16Updated 2 years ago
- mathLab mirror of Python Dynamic Mode Decomposition☆86Updated last month
- Stochastic Optimization under Uncertainty in Python.☆35Updated 8 months ago
- Physics-informed learning of governing equations from scarce data☆11Updated 4 years ago
- Code for the paper "Thermodynamics-informed graph neural networks" published in IEEE Transactions on Artificial Intelligence (TAI).☆96Updated 7 months ago
- Turbulent flow network source code☆68Updated last month
- a novel framework based on a physics-informed neural network dubbed as PhysCon that combines the interpretable ability of physical laws a…☆10Updated 2 years ago
- Physics-Informed Neural Network SurrogaTe for Rapidly Identifying Parameters in Energy Systems☆37Updated 7 months ago
- ☆13Updated 5 years ago
- when using, please cite "Bayesian Physics-Informed Neural Networks for real-world nonlinear dynamical systems", CMAME, https://doi.org/1…☆69Updated 2 years ago
- Drop-in replacements for PyTorch nn.Linear for stable learning and inductive priors in physics informed machine learning applications.☆18Updated last year
- Offshore wind farm wake modelling using deep feed forward neural networks for active yaw control and layout optimisation☆37Updated last year
- Hidden physics models: Machine learning of nonlinear partial differential equations☆145Updated 5 years ago
- ETH Zürich Deep Learning in Scientific Computing Master's course 2023☆109Updated 8 months ago
- One-Shot Transfer Learning of PINNs☆10Updated last year
- ☆20Updated last week
- Source code of: "Manifold learning-based polynomial chaos expansions for high-dimensional surrogate models".☆37Updated 2 years ago