cianmscannell / pinns
Physics-informed neural networks
☆14Updated 4 years ago
Alternatives and similar repositories for pinns:
Users that are interested in pinns are comparing it to the libraries listed below
- XPINN code written in TensorFlow 2☆27Updated 2 years ago
- Discontinuity Computing Using Physics-Informed Neural Network☆23Updated 11 months ago
- Python codes for Locally Adaptive Activation Function (LAAF) used in deep neural networks. Please cite this work as "A D Jagtap, K Kawa…☆39Updated 2 years ago
- ☆25Updated 8 months ago
- Competitive Physics Informed Networks☆27Updated 6 months ago
- A sequential DeepONet model implementation that uses a recurrent neural network (GRU and LSTM) in the branch and a feed-forward neural ne…☆13Updated 11 months ago
- TensorFlow 2.0 implementation of Yibo Yang, Paris Perdikaris’s adversarial Uncertainty Quantification in Physics Informed Neural Networks…☆20Updated 2 years ago
- Sparse Identification of Nonlinear Dynamics for Boundary Value Problems☆12Updated 3 years ago
- Physics-Informed Neural Networks for solving PDEs (bachelor project)☆10Updated 2 years ago
- This repository contains the code and models for our paper "Investigating and Mitigating Failure Modes in Physics-informed Neural Network…☆18Updated last year
- ☆26Updated 2 years ago
- Sample codes of CNN-SINDy based reduced-order modeling for fluid flows by Fukami et al., JFM 2021.☆25Updated 3 years ago
- ☆9Updated last year
- Prediction of Fluid Flow in Porous Media by Sparse Observations and Physics-Informed PointNet☆11Updated 7 months ago
- Introduction to JAX Workshop @ ETH Zurich, 25 June 2024☆26Updated 9 months ago
- Sparse Physics-based and Interpretable Neural Networks☆48Updated 3 years ago
- Physics-informed radial basis network☆30Updated 10 months ago
- Multi-fidelity reduced-order surrogate modeling☆20Updated 3 months ago
- POD-PINN code and manuscript☆50Updated 4 months ago
- Physics-informed graph neural network (GNN) emulation of soft-tissue mechanics☆28Updated 2 weeks ago
- Accelerating Physics Informed Neural Networks (PINNs) using Meshless Discretizations☆25Updated last year
- Derivative-Informed Neural Operator: An Efficient Framework for High-Dimensional Parametric Derivative Learning☆17Updated last year
- Reduced-Order Modeling of Fluid Flows with Transformers☆23Updated last year
- Code for "Robust flow field reconstruction from limited measurements vis sparse representation" (J. Callaham, K. Maeda, and S. Brunton 20…☆14Updated 6 years ago
- Yet another PINN implementation☆20Updated 9 months ago
- Multifidelity DeepONet☆30Updated last year
- This repository contains code, which was used to generate large-scale results in the HINTS paper.☆27Updated 5 months ago
- Code for Mesh Transformer describes in the EAGLE dataset☆38Updated last month
- ☆10Updated last year
- A Self-Training Physics-Informed Neural Network for Partial Differential Equations☆21Updated last year