dynamicslab / databook_pythonLinks
IPython notebooks with demo code intended as a companion to the book "Data-Driven Science and Engineering: Machine Learning, Dynamical Systems, and Control" by Steven L. Brunton and J. Nathan Kutz
β939Updated last year
Alternatives and similar repositories for databook_python
Users that are interested in databook_python are comparing it to the libraries listed below
Sorting:
- All the handwritten notes π and source code files π₯οΈ used in my YouTube Videos on Machine Learning & Simulation (https://www.youtube.coβ¦β1,069Updated 4 months ago
- Matlab files with demo code intended as a companion to the book "Data-Driven Science and Engineering: Machine Learning, Dynamical Systemsβ¦β305Updated last year
- Code accompanying my blog post: So, what is a physics-informed neural network?β643Updated 3 years ago
- IPython notebooks with demo code intended as a companion to the book "Data-Driven Science and Engineering: Machine Learning, Dynamical Syβ¦β157Updated 3 years ago
- A package for the sparse identification of nonlinear dynamical systems from dataβ1,673Updated this week
- Welcome to the Physics-based Deep Learning Book v0.3 - the GenAI Editionβ1,185Updated last month
- Introductory workshop on PINNs using the harmonic oscillatorβ129Updated 5 months ago
- Pytorch-based framework for solving parametric constrained optimization problems, physics-informed system identification, and parametric β¦β1,203Updated last week
- Python Dynamic Mode Decompositionβ1,048Updated last week
- β207Updated last year
- β370Updated 3 years ago
- A library for solving differential equations using neural networks based on PyTorch, used by multiple research groups around the world, iβ¦β764Updated 2 months ago
- Lagrangian Neural Networksβ514Updated 2 weeks ago
- A package for computing data-driven approximations to the Koopman operator.β378Updated 11 months ago
- Scripts and notebooks to accompany the book Data-Driven Methods for Dynamic Systemsβ143Updated 2 months ago
- Physics-Informed Neural networks for Advanced modelingβ574Updated last week
- OSS library that implements deep learning methods for partial differential equations and much moreβ452Updated last week
- Solve forward and inverse problems related to partial differential equations using finite basis physics-informed neural networks (FBPINNsβ¦β457Updated 3 months ago
- A differentiable PDE solving framework for machine learningβ1,701Updated 2 months ago
- Python package for solving partial differential equations using finite differences.β445Updated last week
- ETH ZΓΌrich Deep Learning in Scientific Computing Master's course 2023β117Updated last year
- SINDy-PI: A Robust Algorithm for Parallel Implicit Sparse Identification of Nonlinear Dynamicsβ153Updated 4 years ago
- UQpy (Uncertainty Quantification with python) is a general purpose Python toolbox for modeling uncertainty in physical and mathematical sβ¦β328Updated last month
- ME 539 - Introduction to Scientific Machine Learningβ122Updated last month
- Code for our paper "Hamiltonian Neural Networks"β483Updated 4 years ago
- Source code for 'Dynamical Systems with Applications Using Python' by Stephen Lynchβ154Updated 7 years ago
- β193Updated 2 years ago
- Surrogate Modeling Toolboxβ809Updated this week
- A package for the sparse identification of nonlinear dynamical systems from dataβ11Updated 5 years ago
- PyDEns is a framework for solving Ordinary and Partial Differential Equations (ODEs & PDEs) using neural networksβ313Updated last year