sch0ngut / machine-learning-of-pdes
Code of my master's thesis on "Physics Informed Machine Learning of Nonlinear Partial Differential Equations"
☆9Updated 4 years ago
Alternatives and similar repositories for machine-learning-of-pdes
Users that are interested in machine-learning-of-pdes are comparing it to the libraries listed below
Sorting:
- Simple demo on implementing data driven and physics informed Deep O Nets in pytorch☆11Updated 10 months ago
- The repository contains implementations of examples provided in the literature on energy minimization based approach to Physics Informed …☆11Updated 5 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
- Learning with Higher Expressive Power than Neural Networks (On Learning PDEs)☆15Updated 4 years ago
- Variational Neural Networks for the Solution of Partial Differential Equations☆8Updated 5 years ago
- PDE-VAE: Variational Autoencoder for Extracting Interpretable Physical Parameters from Spatiotemporal Systems using Unsupervised Learning☆35Updated 3 years ago
- Semi-supervised Invertible Neural Operators for Bayesian Inverse Problems☆13Updated 11 months ago
- Learning two-phase microstructure evolution using neural operators and autoencoder architectures☆23Updated last year
- ☆32Updated last year
- ☆41Updated 2 years ago
- TensorFlow 2.0 implementation of Yibo Yang, Paris Perdikaris’s adversarial Uncertainty Quantification in Physics Informed Neural Networks…☆20Updated 2 years ago
- This is the implementation of the RecFNO.☆20Updated 2 years ago
- Fourier Neural Operators to solve for Allen Cahn PDE equations☆18Updated 3 years ago
- ☆9Updated 2 months ago
- ☆12Updated last year
- ☆20Updated 3 years ago
- ☆14Updated last year
- Stochastic Physics-Informed Neural Ordinary Differential Equations☆16Updated 2 years ago
- ☆21Updated 2 years ago
- ☆10Updated 2 years ago
- ☆20Updated last year
- ☆53Updated 2 years ago
- Codes associated with the manuscript titled "Multi-stage neural networks: Function approximator of machine precision"☆43Updated last year
- ☆13Updated 4 years ago
- Different methods of solving partial differential equations with neural networks☆17Updated 3 years ago
- ☆25Updated 2 years ago
- ☆21Updated 4 years ago
- ☆19Updated 3 years ago
- Stochastic Physics-Informed Neural Networks: A Moment-Matching Framework for Learning Hidden Physics within Stochastic Differential Equat…☆14Updated 3 years ago
- Generative Learning for Forecasting the Dynamics of High Dimensional Complex Systems☆29Updated 2 months ago