Alternatives and similar repositories for koopcore

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

• asikist / nnc
  A framework for neural network control of dynamical systems over graphs.
  ☆56Updated 3 years ago
• DiffEqML / torchcontrol
  A PyTorch library for all things nonlinear control and reinforcement learning.
  ☆47Updated 4 years ago
• Machine-Learning-Dynamical-Systems / kooplearn
  A Python package to learn the Koopman operator.
  ☆63Updated last week
• sklus / d3s
  Data-driven dynamical systems toolbox.
  ☆77Updated 3 weeks ago
• ivandariojr / LyapunovLearning
  ☆44Updated 2 years ago
• xl402 / deep-koopman
  IIB Master's Project: Deep Learning for Koopman Optimal Predictive Control
  ☆49Updated 5 years ago
• donken / NeuralOC
  A Neural Network Approach for Real-Time High-Dimensional Optimal Control
  ☆27Updated 3 years ago
• PredictiveIntelligenceLab / GP-NODEs
  ☆28Updated 3 years ago
• YunzhuLi / CompositionalKoopmanOperators
  [ICLR 2020] Learning Compositional Koopman Operators for Model-Based Control
  ☆91Updated 4 years ago
• EthanJamesLew / AutoKoopman
  AutoKoopman - automated Koopman operator methods for data-driven dynamical systems analysis and control.
  ☆79Updated last year
• vmartinezalvarez / DyNODE
  DyNODE: Neural Ordinary Differential Equations for Dynamics Modeling in Continuous Control
  ☆23Updated 5 years ago
• cagatayyildiz / npde
  Nonparametric Differential Equation Modeling
  ☆56Updated last year
• dgedon / DeepSSM_SysID
  Official PyTorch implementation of "Deep State Space Models for Nonlinear System Identification", 2020.
  ☆98Updated 3 years ago
• pnnl / NeuralDAEs
  Learning Neural Differential Algebraic Equations via Operator Splitting
  ☆21Updated 3 months ago
• GaloisInc / dlkoopman
  A general-purpose Python package for Koopman theory using deep learning.
  ☆115Updated last month
• clegaard / deep_learning_for_dynamical_systems
  ☆89Updated 2 years ago
• DesmondZhong / Lagrangian_caVAE
  Official implementation for our paper "Unsupervised Learning of Lagrangian Dynamics from Images for Prediction and Control"
  ☆20Updated 3 years ago
• d-biswa / Symplectic-ODENet
  ☆15Updated 4 years ago
• NoemieJaquier / GaBOtorch
  This repository contains the source code to perform Geometry-aware Bayesian Optimization (GaBO) on Riemannian manifolds.
  ☆53Updated 4 years ago
• wuwushrek / physics_constrained_nn
  Neural Networks with Physics-Informed Architectures and Constraints for Dynamical Systems Modeling
  ☆52Updated 4 years ago
• yuan-yin / APHYNITY
  Augmenting Physical Models with Deep Networks for Complex Dynamics Forecasting
  ☆48Updated last year
• urban-fasel / SEIR_SINDY_MPC
  ☆45Updated 4 years ago
• decargroup / pykoop
  Koopman operator identification library in Python, compatible with `scikit-learn`
  ☆98Updated last month
• samholt / NeuralLaplaceControl
  Neural Laplace Control for Continuous-time Delayed Systems - an offline RL method combining Neural Laplace dynamics model and MPC planner…
  ☆14Updated 2 years ago
• asrvsn / koopman-robust-control
  Uncertainty sets for nonlinear dynamical systems
  ☆10Updated 5 years ago
• JoeMWatson / input-inference-for-control
  Input Inference for Control (i2c), a control-as-inference framework for optimal control
  ☆25Updated 2 years ago
• eurika-kaiser / KRONIC
  Koopman Reduced-Order Nonlinear Identification and Control
  ☆92Updated 5 years ago
• hegdepashupati / gaussian-process-odes
  Implementation of the work Variational multiple shooting for Bayesian ODEs with Gaussian processes
  ☆13Updated 3 years ago
• Physics-aware-AI / DiffCoSim
  By introducing a differentiable contact model, DiffCoSim extends the applicability of Lagrangian/Hamiltonian-inspired neural networks to …
  ☆37Updated 2 years ago
• cagatayyildiz / npode
  Learning unknown ODE models with Gaussian processes
  ☆27Updated 7 years ago