XuhuiM / Multi-Fidelity-DNNs-PINNsLinks
☆37Updated last year
Alternatives and similar repositories for Multi-Fidelity-DNNs-PINNs
Users that are interested in Multi-Fidelity-DNNs-PINNs are comparing it to the libraries listed below
Sorting:
- ☆41Updated 2 years ago
- Multi-fidelity reduced-order surrogate modeling☆24Updated 2 months ago
- multi-fidelity neural network☆20Updated 2 years ago
- Physics-Constrained Bayesian Neural Network for Fluid Flow Reconstruction with Sparse and Noisy Data☆49Updated 5 years ago
- POD-PINN code and manuscript☆52Updated 9 months ago
- Multi-fidelity Gaussian Process☆27Updated 4 years ago
- Pytorch implementation of Bayesian physics-informed neural networks☆61Updated 3 years ago
- A Backward Compatible -- Physics Informed Neural Network for Allen Cahn and Cahn Hilliard Equations☆32Updated 3 years ago
- Source code for POD-DL-ROM: enhancing deep learning-based reduced order models for nonlinear parametrized PDEs by proper orthogonal decom…☆32Updated last year
- Surrogate Modeling for Fluid Flows Based on Physics-Constrained Label-Free Deep Learning☆89Updated 2 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
- Multi-fidelity regression with neural networks☆14Updated 8 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…☆41Updated 2 years ago
- Examplary code for NN, MFNN, DynNet, PINNs and CNN☆50Updated 3 years ago
- ☆63Updated 6 years ago
- Sample codes of CNN-SINDy based reduced-order modeling for fluid flows by Fukami et al., JFM 2021.☆26Updated 3 years ago
- Sparse Physics-based and Interpretable Neural Networks☆51Updated 3 years ago
- ☆19Updated last year
- Multi-fidelity modeling using Gaussian processes and nonlinear auto-regressive schemes.☆66Updated 8 years ago
- Multi-fidelity Bayesian Optimization via Deep Neural Nets☆31Updated 4 years ago
- Gradient-based adaptive sampling algorithms for self-supervising PINNs☆26Updated 2 years ago
- This repository contains the files used in the paper " Reduced-order Model for Fluid Flows via Neural Ordinary Differential Equations"☆19Updated 2 years ago
- A collection of Jupyter notebooks providing tutorials on reduced order modeling techniques like DeepONet, FNO, DL-ROM, and POD-DL-ROM. Ea…☆25Updated 7 months ago
- Physics-guided neural network framework for elastic plates☆45Updated 3 years ago
- Physics-Informed Neural Network (PINN) for Solving Coupled PDEs Governing Thermochemical Physics in Bi-Material Systems☆56Updated 4 years ago
- TensorFlow 2.0 implementation of Yibo Yang, Paris Perdikaris’s adversarial Uncertainty Quantification in Physics Informed Neural Networks…☆20Updated 2 years ago
- ☆129Updated 3 years ago
- To address some of the failure modes in training of physics informed neural networks, a Lagrangian architecture is designed to conform to…☆49Updated 2 years ago
- PhyGeoNet: Physics-Informed Geometry-Adaptive Convolutional Neural Networks for Solving Parametric PDEs on Irregular Domain☆87Updated 4 years ago
- Multi-fidelity probability machine learning☆18Updated 7 months ago