ChrisRackauckas / PINN_Quadrature
Studying quadrature methods applied to PINNs
☆22Updated 2 years ago
Related projects: ⓘ
- ☆30Updated 2 months ago
- Innovative, efficient, and computational-graph-based finite element simulator for inverse modeling☆79Updated 3 years ago
- Deep renormalized Mori-Zwanzig (DrMZ) Julia package.☆11Updated last year
- The unsupervised learning problem trains a diffeomorphic spatio-temporal grid, that registers the output sequence of the PDEs onto a non-…☆16Updated 2 years ago
- Discontinuity Computing Using Physics-Informed Neural Network☆19Updated 5 months ago
- Derivative-Informed Neural Operator: An Efficient Framework for High-Dimensional Parametric Derivative Learning☆18Updated 8 months ago
- Efficient, Accurate, and Streamlined Training of Physics-Informed Neural Networks☆54Updated last week
- TensorFlow 2.0 implementation of Yibo Yang, Paris Perdikaris’s adversarial Uncertainty Quantification in Physics Informed Neural Networks…☆17Updated last year
- Dimension reduced surrogate construction for parametric PDE maps☆36Updated last month
- Convolutional Solvers for Partial Differential Equations☆28Updated 4 years ago
- ☆40Updated 8 months ago
- Sparse Physics-based and Interpretable Neural Networks☆43Updated 2 years ago
- Sparse Identification of Nonlinear Dynamics for Boundary Value Problems☆12Updated 3 years ago
- ☆28Updated 7 months ago
- Efficient and Scalable Physics-Informed Deep Learning and Scientific Machine Learning on top of Tensorflow for multi-worker distributed c…☆110Updated 2 years ago
- ☆31Updated this week
- ☆51Updated 4 months ago
- Accelerating Physics Informed Neural Networks (PINNs) using Meshless Discretizations☆20Updated last year
- Learning Green's functions of partial differential equations with deep learning.☆62Updated 8 months ago
- ☆37Updated 4 years ago
- Multifidelity DeepONet☆25Updated last year
- Numerical Gaussian Processes for Time-dependent and Non-linear Partial Differential Equations☆66Updated 4 years ago
- Neural Network Approach for Data-Driven Constitutive Modeling☆37Updated 2 years ago
- Source code of 'Deep transfer operator learning for partial differential equations under conditional shift'.☆59Updated last year
- Physics-informed convolutional-recurrent neural networks for solving spatiotemporal PDEs☆20Updated 2 years ago
- Predicting parametric spatiotemporal dynamics by multi-resolution PDE structure-preserved deep learning☆10Updated 2 years ago
- ☆28Updated 2 years ago
- ☆13Updated last month
- Stiff Neural Ordinary Differential Equations☆30Updated last year
- ☆13Updated last month