Jianxun-Wang / LabelFree-DNN-SurrogateView external linksLinks
Surrogate Modeling for Fluid Flows Based on Physics-Constrained Label-Free Deep Learning
☆94Aug 17, 2023Updated 2 years ago
Alternatives and similar repositories for LabelFree-DNN-Surrogate
Users that are interested in LabelFree-DNN-Surrogate are comparing it to the libraries listed below
Sorting:
- Physics-Constrained Bayesian Neural Network for Fluid Flow Reconstruction with Sparse and Noisy Data☆50Jul 23, 2020Updated 5 years ago
- PhyGeoNet: Physics-Informed Geometry-Adaptive Convolutional Neural Networks for Solving Parametric PDEs on Irregular Domain☆92Jan 24, 2021Updated 5 years ago
- Physics-constrained deep learning for high-dimensional surrogate modeling and uncertainty quantification without labeled data☆151Oct 18, 2019Updated 6 years ago
- POD-PINN code and manuscript☆57Nov 10, 2024Updated last year
- ☆63Jul 24, 2019Updated 6 years ago
- Bayesian deep convolutional encoder-decoder networks for surrogate modeling and uncertainty quantification☆108Aug 4, 2020Updated 5 years ago
- ☆110Oct 16, 2021Updated 4 years ago
- Physics-constrained auto-regressive convolutional neural networks for dynamical PDEs☆93May 11, 2022Updated 3 years ago
- Physics-informed neural network for solving fluid dynamics problems☆264Jan 28, 2021Updated 5 years ago
- Supporting code for "Reduced-order modeling of advection-dominated systems with recurrent neural networks and convolutional autoencoders"☆21Jan 6, 2021Updated 5 years ago
- physics-informed neural network for elastodynamics problem☆154Jan 20, 2022Updated 4 years ago
- ☆25Oct 15, 2020Updated 5 years ago
- A place to share problems solved with SciANN☆304Nov 6, 2023Updated 2 years ago
- ☆239Oct 14, 2021Updated 4 years ago
- An automatic knowledge embedding framework for scientific machine learning☆23May 15, 2022Updated 3 years ago
- Source code for "Probabilistic neural networks for fluid flow model-order reduction and data recovery"☆11Sep 19, 2020Updated 5 years ago
- Super-resolution and denoising of fluid flow using physics-informed convolutional neural networks without high-resolution labels -- param…☆23Aug 2, 2021Updated 4 years ago
- ☆117Feb 5, 2025Updated last year
- Numerical assessments of a nonintrusive surrogate model based on recurrent neural networks and proper orthogonal decomposition: Rayleigh …☆10Dec 2, 2022Updated 3 years ago
- Source code for POD-DL-ROM: enhancing deep learning-based reduced order models for nonlinear parametrized PDEs by proper orthogonal decom…☆37Sep 7, 2023Updated 2 years ago
- Uncertainty Quantification in the POD-NN framework☆24Sep 10, 2020Updated 5 years ago
- LES-ML closures for Kraichnan turbulence☆19Feb 3, 2020Updated 6 years ago
- Source code for deep learning-based reduced order models in cardiac electrophysiology. Available on doi.org/10.1371/journal.pone.0239416.☆16Sep 7, 2023Updated 2 years ago
- Deep Learning of Vortex Induced Vibrations☆99Feb 21, 2020Updated 5 years ago
- hp-VPINNs: variational physics-informed neural network with domain decomposition is a general framework to solve differential equations☆88Aug 26, 2025Updated 5 months ago
- Source code for deep learning-based reduced order models for nonlinear time-dependent parametrized PDEs. Available on doi.org/10.1007/s10…☆27Sep 7, 2023Updated 2 years ago
- Characterizing possible failure modes in physics-informed neural networks.☆150Nov 18, 2021Updated 4 years ago
- A python implementation of Physics-informed Spline Learning for nonlinear dynamics discovery.☆27Sep 30, 2021Updated 4 years ago
- Extended Physics-Informed Neural Networks (XPINNs): A Generalized Space-Time Domain Decomposition Based Deep Learning Framework for Nonli…☆243Feb 1, 2023Updated 3 years ago
- Multi-fidelity Generative Deep Learning Turbulent Flows☆37Jan 13, 2021Updated 5 years ago
- This repository contains the simple source codes of "Machine-learning-based reduced-order modeling for unsteady flows around bluff bodies…☆17May 14, 2021Updated 4 years ago
- TensorFlow 2.0 implementation of Yibo Yang, Paris Perdikaris’s adversarial Uncertainty Quantification in Physics Informed Neural Networks…☆21Mar 25, 2023Updated 2 years ago
- XPINN code written in TensorFlow 2☆28Feb 1, 2023Updated 3 years ago
- Accelerating Physics Informed Neural Networks (PINNs) using Meshless Discretizations☆33Apr 15, 2023Updated 2 years ago
- Physics-informed graph neural Galerkin networks: A unified framework for solving PDE-governed forward and inverse problems☆59Jan 25, 2022Updated 4 years ago
- Leaning Proper Orthogonal Decomposition coefficients using Deep Neural Networks.☆10Dec 4, 2019Updated 6 years ago
- Repository to reproduce the experiments in the paper "Deep learning observables in computational fluid dynamics"☆14Dec 16, 2019Updated 6 years ago
- Physics-informed learning of governing equations from scarce data☆167Jul 19, 2023Updated 2 years ago
- ☆63Mar 22, 2023Updated 2 years ago