xristosl0610 / PhI-SINDyLinks
Physics Informed Sparse Identification of Nonlinear Dynamics
☆11Updated 10 months ago
Alternatives and similar repositories for PhI-SINDy
Users that are interested in PhI-SINDy are comparing it to the libraries listed below
Sorting:
- Generalized sparse regression for continuous and discrete data☆12Updated 2 weeks ago
- This codes calculates the dimensionalized POD and uses SINDy from the PySINDy python package to build a data-driven model for it. The cod…☆21Updated 4 years ago
- combination of sparse identification of nonlinear dynamics with Akaike information criteria☆16Updated 8 years ago
- KTH-FlowAI / Towards-extraction-of-orthogonal-and-parsimonious-non-linear-modes-from-turbulent-flows☆11Updated 2 years ago
- ☆12Updated last week
- This repository contains the code and models for our paper "Investigating and Mitigating Failure Modes in Physics-informed Neural Network…☆19Updated last year
- SINDy-SA framework: enhancing nonlinear system identification with sensitivity analysis☆12Updated 6 months ago
- ☆15Updated last week
- Solve mass spring damper system with phyics-informed neural networks in MATLAB☆13Updated last year
- Sparse Identification of Nonlinear Dynamics for Boundary Value Problems☆13Updated 4 years ago
- TensorFlow 2.0 implementation of Yibo Yang, Paris Perdikaris’s adversarial Uncertainty Quantification in Physics Informed Neural Networks…☆21Updated 2 years ago
- Official Code for ICML 2024 paper "TENG: Time-Evolving Natural Gradient for Solving PDEs With Deep Neural Nets Toward Machine Precision"☆13Updated 11 months ago
- Implementation of a Physics Informed Neural Network (PINN) written in Tensorflow v2, which is capable of solving Partial Differential Equ…☆15Updated 3 years ago
- ☆12Updated 2 years ago
- ☆14Updated 3 years ago
- Yet another PINN implementation☆20Updated last year
- Deep renormalized Mori-Zwanzig (DrMZ) Julia package.☆17Updated 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
- Operator Inference for data-driven, non-intrusive model reduction of dynamical systems.☆75Updated 3 weeks ago
- Python scripts to run resolution of the Reynolds-Averaged-Navier-Stokes equations over NACA 4 and 5 digits airfoils.☆24Updated 10 months ago
- Physics-Informed Super-Resolution☆10Updated 2 years ago
- Dynamic weight strategy of physics-informed neural networks for the 2D Navier-Stokes equations☆13Updated 3 years ago
- Transformed Generative Pre-Trained Physics-Informed Neural Networks (TGPT-PINN), a framework that extends Physics-Informed Neural Network…☆18Updated last year
- A minimal implementation of Physics-Informed Neural Networks (PINNs) in PyTorch☆20Updated last year
- Bayesian autoencoders for data-driven discovery of coordinates, governing equations and fundamental constants. Proceedings of the Royal S…☆10Updated last year
- Numerical assessments of a nonintrusive surrogate model based on recurrent neural networks and proper orthogonal decomposition: Rayleigh …☆10Updated 2 years ago
- ☆10Updated 2 years ago
- Spectral solution for 2D Navier-Stokes equations☆14Updated 9 years ago
- Source code for deep learning-based reduced order models in cardiac electrophysiology. Available on doi.org/10.1371/journal.pone.0239416.☆15Updated 2 years ago
- ☆14Updated 11 months ago