Alternatives and similar repositories for sysid-transformers

Users that are interested in sysid-transformers are comparing it to the libraries listed below

• bemporad / jax-sysid
  A Python package for linear subspace identification, nonlinear system identification, and nonlinear regression using Jax
  ☆34Updated 2 months ago
• forgi86 / dynonet
  "dynoNet: A neural network architecture for learning dynamical systems" by Marco Forgione and Dario Piga
  ☆44Updated last year
• EthanJamesLew / AutoKoopman
  AutoKoopman - automated Koopman operator methods for data-driven dynamical systems analysis and control.
  ☆73Updated last year
• forgi86 / sysid-transfer-functions-pytorch
  Codes accompanying the paper "Deep learning with transfer functions: new applications in system identification"
  ☆22Updated last year
• forgi86 / pytorch-ident
  System identification in PyTorch
  ☆25Updated 2 years ago
• MaartenSchoukens / deepSI
  Dynamical System Identification using python incorporating numerous powerful deep learning methods. (deepSI = deep System Identification)
  ☆57Updated last month
• wuwushrek / physics_constrained_nn
  Neural Networks with Physics-Informed Architectures and Constraints for Dynamical Systems Modeling
  ☆48Updated 3 years ago
• xl402 / deep-koopman
  IIB Master's Project: Deep Learning for Koopman Optimal Predictive Control
  ☆45Updated 4 years ago
• i-abr / mpc-koopman
  Model-based Control using Koopman Operators
  ☆51Updated 4 years ago
• decargroup / pykoop
  Koopman operator identification library in Python, compatible with `scikit-learn`
  ☆75Updated 3 weeks ago
• FilippoAiraldi / casadi-neural-nets
  Neural Networks with CasADi
  ☆10Updated 2 months ago
• GaloisInc / dlkoopman
  A general-purpose Python package for Koopman theory using deep learning.
  ☆104Updated 3 months ago
• Machine-Learning-Dynamical-Systems / kooplearn
  A Python package to learn the Koopman operator.
  ☆57Updated 6 months ago
• srl-ethz / DeSKO-Deep-Stochastic-Koopman-Operator
  ☆14Updated 3 months ago
• forgi86 / sysid-neural-estimator
  Code accompanying the paper "Learning neural state-space models: do we need a state estimator?"
  ☆10Updated last year
• i-abr / active-learning-koopman
  ☆24Updated 4 years ago
• bemporad / GLIS
  GLIS package
  ☆28Updated 2 years ago
• meco-group / nlgreyfast
  Toolbox for system identification of nonlinear state space grey-box models using CasADi
  ☆25Updated last year
• giorgosmamakoukas / MemoryEfficientStableLDS
  Codebase associated with paper "Memory-Efficient Learning of Stable Linear Dynamical Systems for Prediction and Control"
  ☆24Updated 4 years ago
• asikist / nnc
  A framework for neural network control of dynamical systems over graphs.
  ☆58Updated 2 years ago
• forgi86 / sysid-neural-continuous
  Continuous-time system identification with neural networks
  ☆25Updated 3 years ago
• learning-and-control / core
  Python simulation and hardware library for learning and control
  ☆20Updated 2 years ago
• pnnl / deps_arXiv2020
  Differentiable predictive control (DPC) policy optimization examples.
  ☆53Updated last year
• Pdbz199 / Koopman-RL-Old
  Data-driven Koopman control theory applied to reinforcement learning!
  ☆32Updated last year
• MilanKorda / KoopmanMPC
  ☆72Updated 7 years ago
• bjack205 / BilinearControl.jl
  ☆27Updated 2 years ago
• sklus / d3s
  Data-driven dynamical systems toolbox.
  ☆74Updated 3 weeks ago
• i-abr / TorchMPC
  Pytorch implementation of Model Predictive Control with learned models
  ☆30Updated 4 years ago
• vmartinezalvarez / DyNODE
  DyNODE: Neural Ordinary Differential Equations for Dynamics Modeling in Continuous Control
  ☆23Updated 4 years ago
• lubaroli / dust
  This is the code repository for the DuSt-MPC paper, published at Robotics: Science and Systems (RSS) 2021.
  ☆25Updated 3 years ago