dynamicslab

dynamicslab

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dynamicslab's repositories

pysindy

A package for the sparse identification of nonlinear dynamical systems from data

Language:PythonLicense:NOASSERTIONStargazers:1327Issues:33Issues:334

databook_python

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

Language:Jupyter NotebookStargazers:754Issues:27Issues:0

pykoopman

A package for computing data-driven approximations to the Koopman operator.

Language:PythonLicense:MITStargazers:250Issues:8Issues:27

databook_matlab

Matlab files 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 http://www.databookuw.com/

SINDy-PI

SINDy-PI: A Robust Algorithm for Parallel Implicit Sparse Identification of Nonlinear Dynamics

Language:MATLABLicense:MITStargazers:122Issues:11Issues:5

pysensors

PySensors is a Python package for sparse sensor placement

Language:PythonLicense:MITStargazers:74Issues:10Issues:8

dominant-balance

Methods and code for J. L. Callaham, J. N. Kutz, B. W. Brunton, and S. L. Brunton (2020)

Language:Jupyter NotebookLicense:MITStargazers:54Issues:5Issues:0

modified-SINDy

Example code for paper: Automatic Differentiation to Simultaneously Identify Nonlinear Dynamics and Extract Noise Probability Distributions from Data

Language:Jupyter NotebookLicense:MITStargazers:50Issues:8Issues:0

hydrogym

An RL-Gym for Challenge Problems in Data-Driven Modeling and Control of Fluid Dynamics.

Language:Jupyter NotebookLicense:MITStargazers:43Issues:7Issues:104

langevin-regression

Code for "Nonlinear stochastic modeling with Langevin regression" J. L. Callaham, J.-C. Loiseau, G. Rigas, and S. L. Brunton

Language:Jupyter NotebookStargazers:24Issues:5Issues:0

MultiArm-Pendulum

This repository is for our paper: "The Experimental Multi-Arm Pendulum on a Cart: A Benchmark System for Chaos, Learning, and Control." It contains all the CAD files we used to build the pendulum hardware, their corresponding user's manual, and data set we collected from our hardware, which is useful for Machine Learning and AI community.

Language:MATLABLicense:MITStargazers:19Issues:2Issues:0

deep-learning-fluids

A collection of codes and references for deep learning in fluid dynamics

Language:Jupyter NotebookLicense:MITStargazers:16Issues:5Issues:0

ctf-dl-tutorial

CTF workshop deep learning tutorial and hackathon

Language:Jupyter NotebookStargazers:12Issues:4Issues:0
Language:JuliaLicense:AGPL-3.0Stargazers:2Issues:3Issues:2