mushrafi88 / Physics-Informed-Neural-Networks-for-Quantum-DynamicsLinks
A repo to learn and curate PINN
☆25Updated last year
Alternatives and similar repositories for Physics-Informed-Neural-Networks-for-Quantum-Dynamics
Users that are interested in Physics-Informed-Neural-Networks-for-Quantum-Dynamics are comparing it to the libraries listed below
Sorting:
- Stochastic Physics-Informed Neural Networks: A Moment-Matching Framework for Learning Hidden Physics within Stochastic Differential Equat…☆14Updated 3 years ago
- Solving PDEs with quantum algorithms: A tutorial at IEEE QCE 2023☆22Updated 2 years ago
- FastVPINNs - A tensor-driven acceleration of VPINNs for complex geometries☆46Updated 8 months ago
- Fourier Neural Operators to solve for Allen Cahn PDE equations☆18Updated 3 years ago
- Yet another PINN implementation☆20Updated last year
- This is the repository for the code used in the ICML23 paper called "Achieving High Accuracy with PINNs via Energy Natural Gradient Desce…☆22Updated last year
- This repository contains the code and models for our paper "Investigating and Mitigating Failure Modes in Physics-informed Neural Network…☆19Updated last year
- ETH Zürich AI in the Sciences and Engineering Master's course 2024☆39Updated last year
- 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
- Physics-informed neural networks☆16Updated 4 years ago
- Introductory workshop on using deep neural networks for symbolic regression☆12Updated 6 months ago
- Discontinuity Computing Using Physics-Informed Neural Network☆26Updated last year
- Transformed Generative Pre-Trained Physics-Informed Neural Networks (TGPT-PINN), a framework that extends Physics-Informed Neural Network…☆17Updated last year
- Introduction to JAX Workshop @ ETH Zurich, 25 June 2024☆37Updated 6 months ago
- This repository contains code, which was used to generate large-scale results in the HINTS paper.☆32Updated last year
- XPINN code written in TensorFlow 2☆28Updated 2 years ago
- A Physics-Informed Neural Network for solving Burgers' equation.☆32Updated last year
- In this repository, you will find the different python scripts to train the available models on the AirfRANS dataset proposed at the Neur…☆56Updated 9 months ago
- Theory-guided physics-informed neural networks for boundary layer problems with singular perturbation☆20Updated 2 years ago
- Implementing physics informed neural networks (PINN) in PyTorch to solve turbulent flows using the Navier-Stokes equations☆25Updated last year
- Python script solving the Burgers' equation (équation de Burgers) 1D by using FFT pseudo-spectral method.☆28Updated 4 years ago
- Interactive Jupyter notebooks that illustrate solutions of linear heat, Laplace, transport, and wave equations☆10Updated last year
- Dynamic weight strategy of physics-informed neural networks for the 2D Navier-Stokes equations☆12Updated 3 years ago
- Source code of 'Deep transfer operator learning for partial differential equations under conditional shift'.☆74Updated 2 years ago
- Material for workshop and autumn school on scientific machine learning 2023☆21Updated last year
- Sparse Identification of Nonlinear Dynamics for Boundary Value Problems☆13Updated 4 years ago
- To address some of the failure modes in training of physics informed neural networks, a Lagrangian architecture is designed to conform to…☆50Updated 2 years ago
- ☆28Updated last year
- Bayesian autoencoders for data-driven discovery of coordinates, governing equations and fundamental constants. Proceedings of the Royal S…☆10Updated last year
- ☆12Updated this week