nasa / pigans-material-ID
☆16Updated last year
Alternatives and similar repositories for pigans-material-ID:
Users that are interested in pigans-material-ID are comparing it to the libraries listed below
- ☆14Updated 6 months ago
- A library for dimensionality reduction on spatial-temporal PDE☆62Updated 9 months ago
- hPINN: Physics-informed neural networks with hard constraints☆122Updated 3 years ago
- ☆45Updated last year
- ☆33Updated last month
- Distributed Fourier Neural Operators☆29Updated 2 years ago
- Physics-constrained deep learning for high-dimensional surrogate modeling and uncertainty quantification without labeled data☆141Updated 5 years ago
- Physics-Constrained Bayesian Neural Network for Fluid Flow Reconstruction with Sparse and Noisy Data☆47Updated 4 years ago
- Neural network based solvers for partial differential equations and inverse problems . Implementation of physics-informed neural networks…☆143Updated 2 weeks ago
- The unsupervised learning problem trains a diffeomorphic spatio-temporal grid, that registers the output sequence of the PDEs onto a non-…☆19Updated 2 years ago
- Multifidelity DeepONet☆27Updated last year
- Repo of optimized training recipes for accelerating PyTorch workflows of AI driven surrogates for physical systems☆58Updated last year
- A Python library for reading, writing, finding connectivity for plot3d files☆40Updated 2 weeks ago
- Efficient and Scalable Physics-Informed Deep Learning and Scientific Machine Learning on top of Tensorflow for multi-worker distributed c…☆114Updated 2 years ago
- jupyter notebooks for the neural nets and differential equation paper☆27Updated 3 years ago
- DeepONet extrapolation☆25Updated last year
- ☆62Updated 5 years ago
- Dimension reduced surrogate construction for parametric PDE maps☆38Updated last week
- ODIL (Optimizing a Discrete Loss) is a Python framework for solving inverse and data assimilation problems for partial differential equat…☆99Updated 2 weeks ago
- ☆40Updated 4 years ago
- ☆88Updated 3 years ago
- Physics-informed convolutional-recurrent neural networks for solving spatiotemporal PDEs☆24Updated 3 years ago
- ☆35Updated last year
- ☆25Updated 6 months ago
- Discontinuity Computing Using Physics-Informed Neural Network☆22Updated 9 months ago
- Derivative-Informed Neural Operator: An Efficient Framework for High-Dimensional Parametric Derivative Learning☆17Updated last year
- Surrogate Modeling for Fluid Flows Based on Physics-Constrained Label-Free Deep Learning☆83Updated last year
- Implementation of a Physics Informed Neural Network (PINN) written in Tensorflow v2, which is capable of solving Partial Differential Equ…☆14Updated 2 years ago
- Scientific Machine Learning Tutorials☆36Updated 3 years ago
- Source code for deep learning-based reduced order models for nonlinear time-dependent parametrized PDEs. Available on doi.org/10.1007/s10…☆21Updated last year