li-group / KKThPINNLinks
☆11Updated 6 months ago
Alternatives and similar repositories for KKThPINN
Users that are interested in KKThPINN are comparing it to the libraries listed below
Sorting:
- Workshop tutorials for Pyomo.DoE☆13Updated 2 weeks ago
- Stochastic Optimization under Uncertainty in Python.☆36Updated 3 weeks ago
- Sparse Identification of Nonlinear Dynamics for Boundary Value Problems☆12Updated 4 years ago
- Material for the tutorial on "Physics-Informed Machine Learning (PIML) for Modeling and Control of Dynamical Systems" presented at the Am…☆19Updated last year
- Deep renormalized Mori-Zwanzig (DrMZ) Julia package.☆14Updated 2 years ago
- Transfer learning on PINNs for tracking hemodynamics☆14Updated 10 months ago
- Example code for paper: Automatic Differentiation to Simultaneously Identify Nonlinear Dynamics and Extract Noise Probability Distributio…☆56Updated 3 years ago
- An intuitive modeling interface for infinite dimensional optimization problems.☆11Updated 2 months ago
- multifidelity global sensitivity analysis☆16Updated 2 years ago
- GPTIPS2F: Symbolic Regression toolbox for MATLAB evolved☆11Updated 3 years ago
- Multi-fidelity Bayesian Optimization via Deep Neural Nets☆30Updated 4 years ago
- Computation of invariant manifolds in high-dimensional mechanics problems☆25Updated last year
- To address some of the failure modes in training of physics informed neural networks, a Lagrangian architecture is designed to conform to…☆49Updated 2 years ago
- ☆32Updated 11 months ago
- Multi-fidelity reduced-order surrogate modeling☆23Updated last week
- FOQUS: Framework for Optimization and Quantification of Uncertainty and Surrogates☆47Updated 3 weeks ago
- Studying quadrature methods applied to PINNs☆26Updated 3 years ago
- ☆10Updated 2 years ago
- ☆15Updated last year
- Drop-in replacements for PyTorch nn.Linear for stable learning and inductive priors in physics informed machine learning applications.☆18Updated last year
- This repository contains code, which was used to generate large-scale results in the HINTS paper.☆30Updated 8 months ago
- ☆21Updated 4 years ago
- Derivative-Informed Neural Operator: An Efficient Framework for High-Dimensional Parametric Derivative Learning☆16Updated last year
- ☆12Updated 2 years ago
- ☆10Updated 5 years 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…☆20Updated 4 years ago
- Constructing linearizing transformations for reduced-order modeling of nonlinear dynamical systems☆10Updated 11 months ago
- ☆10Updated 2 years ago
- Dasslc is a solver for differential-algebraic equations inspired by DASSL. A python module for dasslc is provided.☆16Updated last year
- TensorFlow 2.0 implementation of Yibo Yang, Paris Perdikaris’s adversarial Uncertainty Quantification in Physics Informed Neural Networks…☆20Updated 2 years ago