YuntianChen / Hard_constraint_projection_HCPLinks
Theory-guided hard constraint projection (HCP): a knowledge-based data-driven scientific machine learning method
☆63Updated 3 years ago
Alternatives and similar repositories for Hard_constraint_projection_HCP
Users that are interested in Hard_constraint_projection_HCP are comparing it to the libraries listed below
Sorting:
- A python implementation of Physics-informed Spline Learning for nonlinear dynamics discovery.☆27Updated 4 years ago
- Physics-encoded recurrent convolutional neural network☆47Updated 3 years ago
- Physics-informed convolutional-recurrent neural networks for solving spatiotemporal PDEs☆165Updated last year
- Examplary code for NN, MFNN, DynNet, PINNs and CNN☆51Updated 4 years ago
- Pytorch implementation of Bayesian physics-informed neural networks☆66Updated 4 years ago
- Source code of 'Deep transfer operator learning for partial differential equations under conditional shift'.☆75Updated 2 years ago
- Implementation of the Deep Ritz method and the Deep Galerkin method☆61Updated 5 years ago
- Sparse Physics-based and Interpretable Neural Networks☆52Updated 4 years ago
- PhyGeoNet: Physics-Informed Geometry-Adaptive Convolutional Neural Networks for Solving Parametric PDEs on Irregular Domain☆89Updated 4 years ago
- hp-VPINNs: variational physics-informed neural network with domain decomposition is a general framework to solve differential equations☆86Updated 3 months ago
- Surrogate Modeling for Fluid Flows Based on Physics-Constrained Label-Free Deep Learning☆93Updated 2 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…☆43Updated 2 years ago
- Gradient-enhanced physics-informed neural networks for forward and inverse PDE problems☆105Updated 3 years ago
- Physics-constrained deep learning for high-dimensional surrogate modeling and uncertainty quantification without labeled data☆150Updated 6 years ago
- MIONet: Learning multiple-input operators via tensor product☆39Updated 3 years ago
- Physics-informed graph neural Galerkin networks: A unified framework for solving PDE-governed forward and inverse problems☆57Updated 3 years ago
- Physics Informed Fourier Neural Operator☆24Updated last year
- ☆67Updated 3 years ago
- Simple demo on implementing data driven and physics informed Deep O Nets in pytorch☆19Updated last year
- Physics-Constrained Bayesian Neural Network for Fluid Flow Reconstruction with Sparse and Noisy Data☆49Updated 5 years ago
- hPINN: Physics-informed neural networks with hard constraints☆150Updated 4 years ago
- We introduce an innovative physics-informed LSTM framework for metamodeling of nonlinear structural systems with scarce data.☆97Updated 2 years ago
- ☆39Updated 2 years ago
- Accelerating Physics Informed Neural Networks (PINNs) using Meshless Discretizations☆31Updated 2 years ago
- ☆65Updated 3 years ago
- Deep identification of symbolic open-form PDEs via enhanced reinforcement-learning☆39Updated 11 months ago
- Multifidelity deep neural operators for efficient learning of partial differential equations with application to fast inverse design of n…☆35Updated 2 years ago
- ☆63Updated 6 years ago
- Modified Meshgraphnets with more features☆57Updated 10 months ago
- Official implementation of "PhyGNNet: Solving spatiotemporal PDEs with Physics-informed Graph Neural Network"☆53Updated 2 years ago