lu-group / multifidelity-deeponetLinks
Multifidelity deep neural operators for efficient learning of partial differential equations with application to fast inverse design of nanoscale heat transport
☆37Updated 2 years ago
Alternatives and similar repositories for multifidelity-deeponet
Users that are interested in multifidelity-deeponet are comparing it to the libraries listed below
Sorting:
- MIONet: Learning multiple-input operators via tensor product☆42Updated 3 years ago
- POD-PINN code and manuscript☆57Updated last year
- A Backward Compatible -- Physics Informed Neural Network for Allen Cahn and Cahn Hilliard Equations☆36Updated 3 years ago
- Physics-informed graph neural Galerkin networks: A unified framework for solving PDE-governed forward and inverse problems☆57Updated 3 years ago
- Reliable extrapolation of deep neural operators informed by physics or sparse observations☆28Updated 2 years ago
- Sparse Physics-based and Interpretable Neural Networks☆52Updated 4 years ago
- ☆54Updated 3 years ago
- A sequential DeepONet model implementation that uses a recurrent neural network (GRU and LSTM) in the branch and a feed-forward neural ne…☆18Updated last year
- Multi-fidelity reduced-order surrogate modeling☆28Updated 6 months ago
- PhyGeoNet: Physics-Informed Geometry-Adaptive Convolutional Neural Networks for Solving Parametric PDEs on Irregular Domain☆91Updated 4 years ago
- XPINN code written in TensorFlow 2☆28Updated 2 years ago
- Source code of 'Deep transfer operator learning for partial differential equations under conditional shift'.☆75Updated 2 years ago
- In this repository, you will find the different python scripts to train the available models on the AirfRANS dataset proposed at the Neur…☆57Updated 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
- Reduced-Order Modeling of Fluid Flows with Transformers☆24Updated 2 years ago
- Competitive Physics Informed Networks☆32Updated last year
- hp-VPINNs: variational physics-informed neural network with domain decomposition is a general framework to solve differential equations☆86Updated 4 months ago
- Implementation of 'Physics-Informed Neural Networks for Shell Structures' (European Journal of Mechanics A)☆44Updated last year
- A collection of Jupyter notebooks providing tutorials on reduced order modeling techniques like DeepONet, FNO, DL-ROM, and POD-DL-ROM. Ea…☆27Updated 11 months ago
- PDE Preserved Neural Network☆59Updated 7 months ago
- Discontinuity Computing Using Physics-Informed Neural Network☆26Updated last year
- Surrogate Modeling for Fluid Flows Based on Physics-Constrained Label-Free Deep Learning☆93Updated 2 years ago
- Coupled-Automatic-Numerical differentiation scheme for physics-informed neural network (can-PINN)☆33Updated 2 years ago
- ☆44Updated 3 years ago
- ☆33Updated 11 months ago
- Source code for POD-DL-ROM: enhancing deep learning-based reduced order models for nonlinear parametrized PDEs by proper orthogonal decom…☆35Updated 2 years ago
- PINNs for 2D Incompressible Navier-Stokes Equation☆57Updated last year
- This repository contains the code and models for our paper "Investigating and Mitigating Failure Modes in Physics-informed Neural Network…☆19Updated 2 years ago
- Gradient-enhanced physics-informed neural networks for forward and inverse PDE problems☆106Updated 3 years ago
- Physics-guided neural network framework for elastic plates☆48Updated 3 years ago