RuiyangLi6 / PINN-pBTE-deltaTLinks
☆13Updated 3 years ago
Alternatives and similar repositories for PINN-pBTE-deltaT
Users that are interested in PINN-pBTE-deltaT are comparing it to the libraries listed below
Sorting:
- The repository contains implementations of examples provided in the literature on energy minimization based approach to Physics Informed …☆11Updated 5 years ago
- Source code of 'Deep transfer operator learning for partial differential equations under conditional shift'.☆74Updated 2 years ago
- Coupled-Automatic-Numerical differentiation scheme for physics-informed neural network (can-PINN)☆32Updated last year
- Competitive Physics Informed Networks☆31Updated last year
- Rheology-informed Machine Learning Projects☆21Updated last year
- A python implementation of Physics-informed Spline Learning for nonlinear dynamics discovery.☆27Updated 4 years ago
- Simple demo on implementing data driven and physics informed Deep O Nets in pytorch☆19Updated last year
- Contains implementation of PINN using Tensorflow 2.4.0☆14Updated 2 years ago
- Physics-Informed and Hybrid Machine Learning in Additive Manufacturing: Application to Fused Filament Fabrication☆19Updated 3 years ago
- A Backward Compatible -- Physics Informed Neural Network for Allen Cahn and Cahn Hilliard Equations☆34Updated 3 years ago
- ☆19Updated last year
- Code accompanying the manuscript "Augmented Physics-Informed Neural Networks (APINNs): A gating network-based soft domain decomposition m…☆15Updated 2 years ago
- Physics-informed graph neural Galerkin networks: A unified framework for solving PDE-governed forward and inverse problems☆57Updated 3 years ago
- XPINN code written in TensorFlow 2☆28Updated 2 years ago
- Physics-informed radial basis network☆32Updated last year
- ☆12Updated 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…☆43Updated 2 years ago
- ☆29Updated 3 years ago
- Multifidelity deep neural operators for efficient learning of partial differential equations with application to fast inverse design of n…☆35Updated 2 years ago
- Official repo for separable operator networks -- extreme-scale operator learning for parametric PDEs.☆33Updated last year
- This repository includes the implementation of the Physics Informed Neural Network and The Deep Energy Method on 1D, 2D boundary value an…☆15Updated 3 years ago
- This repository contains code, which was used to generate large-scale results in the HINTS paper.☆33Updated last year
- ☆34Updated 3 years ago
- A novel DeepONet architecture that is specifically designed for generating predictions on different 3D geometries discretized by differen…☆21Updated last year
- ☆33Updated 4 months ago
- ☆32Updated 3 years ago
- Implementation of 'Physics-Informed Neural Networks for Shell Structures' (European Journal of Mechanics A)☆44Updated last year
- Yet another PINN implementation☆20Updated last year
- Extraction of mechanical properties of materials through deep learning from instrumented indentation☆71Updated 3 years ago
- Physics-informed convolutional-recurrent neural networks for solving spatiotemporal PDEs☆30Updated 3 years ago