XuhuiM / Multi-Fidelity-DNNs-PINNs
☆35Updated 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
- ☆35Updated last year
- multi-fidelity neural network☆17Updated last year
- POD-PINN code and manuscript☆47Updated 3 months ago
- Physics-Constrained Bayesian Neural Network for Fluid Flow Reconstruction with Sparse and Noisy Data☆47Updated 4 years ago
- Multi-fidelity reduced-order surrogate modeling☆19Updated 2 months ago
- Multi-fidelity regression with neural networks☆11Updated 2 months ago
- Multi-fidelity Gaussian Process☆25Updated 4 years ago
- Physics-guided neural network framework for elastic plates☆34Updated 2 years ago
- A Backward Compatible -- Physics Informed Neural Network for Allen Cahn and Cahn Hilliard Equations☆27Updated 3 years ago
- Pytorch implementation of Bayesian physics-informed neural networks☆50Updated 3 years ago
- ☆17Updated 11 months ago
- Multi-fidelity classification with Gaussian process☆15Updated last year
- Multi-fidelity probability machine learning☆17Updated last month
- Multifidelity DeepONet☆27Updated last year
- Reproduce the first two numerical experiments(Pytorch)☆26Updated 4 years ago
- Physics-Informed Neural Network (PINN) for Solving Coupled PDEs Governing Thermochemical Physics in Bi-Material Systems☆50Updated 4 years ago
- ☆34Updated 2 years ago
- Proper Orthogonal Decomposition - Radial Basis Function (POD-RBF) Network☆59Updated last year
- Examplary code for NN, MFNN, DynNet, PINNs and CNN☆49Updated 3 years ago
- Source code for POD-DL-ROM: enhancing deep learning-based reduced order models for nonlinear parametrized PDEs by proper orthogonal decom…☆29Updated last year
- Non-adaptive and residual-based adaptive sampling for PINNs☆65Updated 2 years ago
- ☆62Updated 5 years ago
- Python codes for Locally Adaptive Activation Function (LAAF) used in deep neural networks. Please cite this work as "A D Jagtap, K Kawa…☆38Updated 2 years ago
- Sample codes of CNN-SINDy based reduced-order modeling for fluid flows by Fukami et al., JFM 2021.☆24Updated 3 years ago
- GCA-ROM is a library which implements graph convolutional autoencoder architecture as a nonlinear model order reduction strategy.☆31Updated 7 months ago
- Surrogate Modeling for Fluid Flows Based on Physics-Constrained Label-Free Deep Learning☆83Updated last year
- Contains implementation of PINN using Tensorflow 2.4.0☆14Updated last year
- Code for 'Physics-Informed Neural Networks for Shell Structures'☆34Updated 6 months ago
- Sparse Physics-based and Interpretable Neural Networks☆47Updated 3 years ago
- Examples implementing physics-informed neural networks (PINN) in Pytorch☆62Updated 3 years ago