KindXiaoming / schrodinger-pca
Schrodinger Principal Component Analysis
☆22Updated 4 years ago
Alternatives and similar repositories for schrodinger-pca:
Users that are interested in schrodinger-pca are comparing it to the libraries listed below
- Counting the number of conservation laws from trajectory data☆21Updated 4 years ago
- Physics Informed Neural Networks (PINNs) + SPINNs + HyperPINNs with JAX 📓 Check out our various notebooks to get started ⚠️ Mirror repos…☆28Updated this week
- Code for "Nonlinear stochastic modeling with Langevin regression" J. L. Callaham, J.-C. Loiseau, G. Rigas, and S. L. Brunton☆25Updated 3 years ago
- This repo contains the code for solving Poisson Equation using Physics Informed Neural Networks☆13Updated 2 years ago
- ☆32Updated last year
- Solving High Dimensional Partial Differential Equations with Deep Neural Networks☆34Updated 3 years ago
- ☆16Updated 8 months ago
- Suite of utilities aiming to simplify the workflow required to build models using Physics Informed Neural Networks and, eventually, Phys…☆26Updated last year
- Datasets and code for results presented in the BOON paper☆43Updated 2 years ago
- Introduction to JAX Workshop @ ETH Zurich, 25 June 2024☆33Updated last week
- Computers, Waves, Simulations: A Practical Introduction to Numerical Methods using Python☆14Updated 5 years ago
- This repository introduces Partial Differential Equation Solver using neural network that can learn resolution-invariant solution operato…☆16Updated 3 years ago
- FastVPINNs - A tensor-driven acceleration of VPINNs for complex geometries☆39Updated 2 months ago
- ☆32Updated 9 months ago
- ☆33Updated 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…☆19Updated 3 years ago
- Using NVIDIA modulus for airfoil optimizations at different angles.☆22Updated 2 years ago
- Simulation-Enabled Prediction, Inference, and Analysis: physics-informed statistical learning.☆35Updated last year
- Neural network based solvers for partial differential equations and inverse problems . Implementation of physics-informed neural networks…☆17Updated 2 years ago
- ☆17Updated 6 months ago
- A curated list of awesome Scientific Machine Learning (SciML) papers, resources and software☆51Updated last year
- TensorFlow PINN study for a couple of Fokker-Planck equations.☆11Updated 2 years ago
- ☆47Updated last year
- To address some of the failure modes in training of physics informed neural networks, a Lagrangian architecture is designed to conform to…☆48Updated 2 years ago
- PySpectral is a Python package for solving the partial differential equation (PDE) of Burgers' equation in its deterministic and stochast…☆14Updated 2 years ago
- Basic implementation of physics-informed neural networks for solving differential equations☆85Updated 4 months ago
- Sample codes for training of Voronoi-tessellation-assisted convolutional neural network by Fukami et al. (Nature Machine Intelligence 202…☆47Updated last year
- Kolmogorov-Arnold Networks (KAN) using orthogonal polynomials instead of B-splines.☆36Updated 5 months ago
- combination of sparse identification of nonlinear dynamics with Akaike information criteria☆16Updated 7 years ago
- Bayesian optimized physics-informed neural network for parameter estimation☆27Updated 5 months ago