Alternatives and similar repositories for EKF-SINDy

Users that are interested in EKF-SINDy are comparing it to the libraries listed below

• decargroup / pykoop
  Koopman operator identification library in Python, compatible with `scikit-learn`
  ☆80Updated last month
• dynamicslab / modified-SINDy
  Example code for paper: Automatic Differentiation to Simultaneously Identify Nonlinear Dynamics and Extract Noise Probability Distributio…
  ☆56Updated 3 years ago
• dynamicslab / SINDy-PI
  SINDy-PI: A Robust Algorithm for Parallel Implicit Sparse Identification of Nonlinear Dynamics
  ☆148Updated 3 years ago
• urban-fasel / SEIR_SINDY_MPC
  ☆44Updated 3 years ago
• eurika-kaiser / KRONIC
  Koopman Reduced-Order Nonlinear Identification and Control
  ☆90Updated 5 years ago
• haozhg / oml
  AI4Science: Efficient data-driven Online Model Learning (OML) / system identification and control
  ☆30Updated 2 years ago
• haller-group / SSMLearn
  Data-driven reduced order modeling for nonlinear dynamical systems
  ☆82Updated 2 weeks ago
• urban-fasel / EnsembleSINDy
  ☆22Updated 3 years ago
• clegaard / deep_learning_for_dynamical_systems
  ☆87Updated 2 years ago
• GaloisInc / dlkoopman
  A general-purpose Python package for Koopman theory using deep learning.
  ☆103Updated 4 months ago
• AleksandarHaber / Subspace-Identification-State-Space-System-Identification-of-Dynamical-Systems-and-Time-Series-
  ☆46Updated 3 months ago
• sklus / d3s
  Data-driven dynamical systems toolbox.
  ☆74Updated last month
• EthanJamesLew / AutoKoopman
  AutoKoopman - automated Koopman operator methods for data-driven dynamical systems analysis and control.
  ☆76Updated last year
• MaartenSchoukens / deepSI
  Dynamical System Identification using python incorporating numerous powerful deep learning methods. (deepSI = deep System Identification)
  ☆58Updated 2 months ago
• AleksandarHaber / Machine-Learning-of-Dynamical-Systems-using-Recurrent-Neural-Networks
  This project deals with learning to reproduce the input-output behavior of state-space models using recurrent neural networks and the Ker…
  ☆33Updated 3 months ago
• forgi86 / dynonet
  "dynoNet: A neural network architecture for learning dynamical systems" by Marco Forgione and Dario Piga
  ☆44Updated last year
• haller-group / SSMLearnPy
  Data-driven reduced order modeling for nonlinear dynamical systems
  ☆30Updated this week
• paulpuren / PhyCRNet
  Physics-informed convolutional-recurrent neural networks for solving spatiotemporal PDEs
  ☆31Updated 3 years ago
• drgona / PIML_ACC2023
  Material for the tutorial on "Physics-Informed Machine Learning (PIML) for Modeling and Control of Dynamical Systems" presented at the Am…
  ☆19Updated last year
• mathLab / PyDMD
  mathLab mirror of Python Dynamic Mode Decomposition
  ☆95Updated 3 months ago
• Jonas-Nicodemus / PINNs-based-MPC
  We discuss nonlinear model predictive control (NMPC) for multi-body dynamics via physics-informed machine learning methods. Physics-infor…
  ☆109Updated last year
• loiseaujc / SINDy
  ☆41Updated 7 years ago
• hyumo / pysindy-gui
  PySINDy GUI
  ☆39Updated 2 years ago
• StanfordASL / rompc
  Reduced Order Model Predictive Control
  ☆24Updated 3 years ago
• dynamicslab / hydrogym
  An RL-Gym for Challenge Problems in Data-Driven Modeling and Control of Fluid Dynamics.
  ☆75Updated last week
• andreikitaitsev / SymINDy
  Symbolic Identification of Non-linear Dynamics. The method generalizes the SINDy algorithm by combining sparse and genetic-programming-ba…
  ☆76Updated 2 years ago
• baddoo / piDMD
  MATLAB codes for physics-informed dynamic mode decomposition (piDMD)
  ☆150Updated last year
• dynamicslab / pykoopman
  A package for computing data-driven approximations to the Koopman operator.
  ☆363Updated 7 months ago
• Baldea-Group / DySMHO
  ☆10Updated 2 years ago
• VVeida / RK4_PINN
  ☆11Updated last year