Alternatives and similar repositories for pysindy

Users that are interested in pysindy are comparing it to the libraries listed below

• dynamicslab / SINDy-PI
  SINDy-PI: A Robust Algorithm for Parallel Implicit Sparse Identification of Nonlinear Dynamics
  ☆161Updated 4 years ago
• dynamicslab / modified-SINDy
  Example code for paper: Automatic Differentiation to Simultaneously Identify Nonlinear Dynamics and Extract Noise Probability Distributio…
  ☆61Updated 3 years ago
• dynamicslab / pykoopman
  A package for computing data-driven approximations to the Koopman operator.
  ☆406Updated 3 weeks ago
• mathLab / PyDMD
  mathLab mirror of Python Dynamic Mode Decomposition
  ☆113Updated 11 months ago
• dynamicslab / dominant-balance
  Methods and code for J. L. Callaham, J. N. Kutz, B. W. Brunton, and S. L. Brunton (2020)
  ☆62Updated 5 years ago
• baddoo / piDMD
  MATLAB codes for physics-informed dynamic mode decomposition (piDMD)
  ☆163Updated last year
• luckystarufo / pySINDy
  SINDy (Sparse Identification of Nonlinear Dynamics) algorithms
  ☆79Updated 3 years ago
• kpchamp / SindyAutoencoders
  ☆379Updated 4 years ago
• snagcliffs / PDE-FIND
  ☆274Updated 3 years ago
• operator-inference / opinf
  Operator Inference for data-driven, non-intrusive model reduction of dynamical systems.
  ☆79Updated 3 weeks ago
• baddoo / LANDO
  Codes for Linear and Nonlinear Disambiguation Optimization (LANDO)
  ☆32Updated 4 years ago
• dynamicslab / hydrogym
  An RL-Gym for Challenge Problems in Data-Driven Modeling and Control of Fluid Dynamics.
  ☆93Updated 3 weeks ago
• andreikitaitsev / SymINDy
  Symbolic Identification of Non-linear Dynamics. The method generalizes the SINDy algorithm by combining sparse and genetic-programming-ba…
  ☆85Updated 3 years ago
• ASEM000 / Physics-informed-neural-network-in-JAX
  Example problems in Physics informed neural network in JAX
  ☆81Updated 2 years ago
• janblechschmidt / PDEsByNNs
  This repository contains a number of Jupyter Notebooks illustrating different approaches to solve partial differential equations by means…
  ☆181Updated 4 years ago
• maziarraissi / MultistepNNs
  Multistep Neural Networks for Data-driven Discovery of Nonlinear Dynamical Systems
  ☆63Updated 5 years ago
• BethanyL / DeepKoopman
  neural networks to learn Koopman eigenfunctions
  ☆467Updated last year
• Crunch-UQ4MI / neuraluq
  ☆200Updated 10 months ago
• maziarraissi / HPM
  Hidden physics models: Machine learning of nonlinear partial differential equations
  ☆149Updated 5 years ago
• loiseaujc / SINDy
  ☆44Updated 8 years ago
• maziarraissi / FBSNNs
  Forward-Backward Stochastic Neural Networks: Deep Learning of High-dimensional Partial Differential Equations
  ☆156Updated 5 years ago
• rezaakb / pinns-jax
  PINNs-JAX, Physics-informed Neural Networks (PINNs) implemented in JAX.
  ☆58Updated last year
• jbramburger / DataDrivenDynSyst
  Scripts and notebooks to accompany the book Data-Driven Methods for Dynamic Systems
  ☆157Updated 3 months ago
• MColbrook / Residual-Dynamic-Mode-Decomposition
  Code for ResDMD: data-driven spectral properties of Koopman Operators
  ☆42Updated last year
• leakec / tfc
  The Theory of Functional Connections: A functional interpolation method with applications in solving differential equations.
  ☆41Updated last month
• josephbakarji / deep-delay-autoencoder
  Discovers high dimensional models from 1D data using deep delay autoencoders
  ☆38Updated 2 years ago
• maziarraissi / NumericalGP
  Numerical Gaussian Processes for Time-dependent and Non-linear Partial Differential Equations
  ☆69Updated 5 years ago
• dynamicslab / pysensors
  PySensors is a Python package for sparse sensor placement
  ☆110Updated 2 weeks ago
• opaliss / dmd_autoencoder
  Enhancing Dynamic Mode Decomposition using Autoencoder Networks.
  ☆35Updated 4 years ago
• dynamicslab / langevin-regression
  Code for "Nonlinear stochastic modeling with Langevin regression" J. L. Callaham, J.-C. Loiseau, G. Rigas, and S. L. Brunton
  ☆27Updated 3 years ago