Alternatives and similar repositories for koopcore:

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

• Machine-Learning-Dynamical-Systems / kooplearn
  A Python package to learn the Koopman operator.
  ☆53Updated 3 months ago
• EthanJamesLew / AutoKoopman
  AutoKoopman - automated Koopman operator methods for data-driven dynamical systems analysis and control.
  ☆69Updated 10 months ago
• PredictiveIntelligenceLab / GP-NODEs
  ☆28Updated 2 years ago
• hegdepashupati / gaussian-process-odes
  Implementation of the work Variational multiple shooting for Bayesian ODEs with Gaussian processes
  ☆12Updated 2 years ago
• donken / NeuralOC
  A Neural Network Approach for Real-Time High-Dimensional Optimal Control
  ☆26Updated 2 years ago
• asikist / nnc
  A framework for neural network control of dynamical systems over graphs.
  ☆57Updated 2 years ago
• xl402 / deep-koopman
  IIB Master's Project: Deep Learning for Koopman Optimal Predictive Control
  ☆45Updated 4 years ago
• DiffEqML / torchcontrol
  A PyTorch library for all things nonlinear control and reinforcement learning.
  ☆45Updated 3 years ago
• decargroup / pykoop
  Koopman operator identification library in Python, compatible with `scikit-learn`
  ☆68Updated 3 months ago
• sklus / d3s
  Data-driven dynamical systems toolbox.
  ☆73Updated 3 weeks ago
• wzhi / ODElearning_INN
  [ICML 2022] Learning Efficient and Robust Ordinary Differential \\ Equations via Invertible Neural Networks
  ☆10Updated last year
• DesmondZhong / Lagrangian_caVAE
  Official implementation for our paper "Unsupervised Learning of Lagrangian Dynamics from Images for Prediction and Control"
  ☆18Updated 2 years ago
• d-biswa / Symplectic-ODENet
  ☆15Updated 4 years ago
• ivandariojr / LyapunovLearning
  ☆39Updated last year
• dmusekamp / al4pde
  AL4PDE: A Benchmark for Active Learning for Neural PDE Solvers
  ☆18Updated last week
• vmartinezalvarez / DyNODE
  DyNODE: Neural Ordinary Differential Equations for Dynamics Modeling in Continuous Control
  ☆22Updated 4 years ago
• cagatayyildiz / npde
  Nonparametric Differential Equation Modeling
  ☆53Updated last year
• wuwushrek / physics_constrained_nn
  Neural Networks with Physics-Informed Architectures and Constraints for Dynamical Systems Modeling
  ☆46Updated 3 years ago
• NoemieJaquier / GaBOtorch
  This repository contains the source code to perform Geometry-aware Bayesian Optimization (GaBO) on Riemannian manifolds.
  ☆51Updated 3 years ago
• sisl / variational_koopman
  Source code for "Deep Variational Koopman Models: Inferring Koopman Observations for Uncertainty-Aware Dynamics Modeling and Control" fro…
  ☆37Updated 5 years ago
• yuan-yin / APHYNITY
  Augmenting Physical Models with Deep Networks for Complex Dynamics Forecasting
  ☆43Updated last year
• william-redman / Koopman-Neural-Network-Training
  Software to train neural networks via Koopman operator theory (see Dogra and Redman "Optimizing Neural Networks via Koopman Operator Theo…
  ☆19Updated last year
• GaloisInc / dlkoopman
  A general-purpose Python package for Koopman theory using deep learning.
  ☆96Updated last month
• locuslab / stable_dynamics
  Companion code to "Learning Stable Deep Dynamics Models" (Manek and Kolter, 2019)
  ☆32Updated 5 years ago
• urban-fasel / SEIR_SINDY_MPC
  ☆41Updated 3 years ago
• i-abr / mpc-koopman
  Model-based Control using Koopman Operators
  ☆51Updated 4 years ago
• YunzhuLi / CompositionalKoopmanOperators
  [ICLR 2020] Learning Compositional Koopman Operators for Model-Based Control
  ☆88Updated 3 years ago
• erichson / koopmanAE
  Consistent Koopman Autoencoders
  ☆71Updated last year
• spenrich / Learning-Control-Oriented-Structure
  Code for "Learning Control-Oriented Dynamical Structure from Data" by Spencer M. Richards, Jean-Jacques Slotine, Navid Azizan, and Marco …
  ☆14Updated last year
• cagatayyildiz / npode
  Learning unknown ODE models with Gaussian processes
  ☆26Updated 6 years ago