Alternatives and similar repositories for Incremental-Gaussian-Process-Regression-IGPR

Users that are interested in Incremental-Gaussian-Process-Regression-IGPR are comparing it to the libraries listed below

• sorooshafiee / WKF
  ☆16Updated 7 years ago
• i-abr / active-learning-koopman
  ☆27Updated 4 years ago
• dgedon / DeepSSM_SysID
  Official PyTorch implementation of "Deep State Space Models for Nonlinear System Identification", 2020.
  ☆99Updated 3 years ago
• fmeier / local_gaussian_regression
  ☆11Updated 7 years ago
• NoemieJaquier / GaBOtorch
  This repository contains the source code to perform Geometry-aware Bayesian Optimization (GaBO) on Riemannian manifolds.
  ☆54Updated 4 years ago
• vmartinezalvarez / DyNODE
  DyNODE: Neural Ordinary Differential Equations for Dynamics Modeling in Continuous Control
  ☆23Updated 5 years ago
• Stanford-ILIAD / active-preference-based-gpr
  Companion code for RSS 2020 paper: "Active Preference-Based Gaussian Process Regression for Reward Learning"
  ☆39Updated last year
• aidanscannell / mogpe
  Mixtures of Gaussian Process Experts in GPflow/TensorFlow
  ☆12Updated 3 years ago
• i-abr / mpc-koopman
  Model-based Control using Koopman Operators
  ☆57Updated 5 years ago
• xl402 / deep-koopman
  IIB Master's Project: Deep Learning for Koopman Optimal Predictive Control
  ☆50Updated 5 years ago
• pnnl / deps_arXiv2020
  Differentiable predictive control (DPC) policy optimization examples.
  ☆60Updated 2 years ago
• asikist / nnc
  A framework for neural network control of dynamical systems over graphs.
  ☆56Updated 3 years ago
• thangbui / streaming_sparse_gp
  Streaming sparse Gaussian process approximations
  ☆69Updated 3 years ago
• YunzhuLi / CompositionalKoopmanOperators
  [ICLR 2020] Learning Compositional Koopman Operators for Model-Based Control
  ☆93Updated 4 years ago
• sisl / variational_koopman
  Source code for "Deep Variational Koopman Models: Inferring Koopman Observations for Uncertainty-Aware Dynamics Modeling and Control" fro…
  ☆43Updated 6 years ago
• i-abr / TorchMPC
  Pytorch implementation of Model Predictive Control with learned models
  ☆30Updated 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
• locuslab / robust-nn-control
  Enforcing robust control guarantees within neural network policies
  ☆55Updated 4 years ago
• Cafolkes / keedmd
  Repository for construction of Koopman eigenfunctions for unknown dynamical systems and identification of a lifted state-space model usin…
  ☆29Updated 3 years ago
• williamedwards / autompc
  Automatic Tuning for Data-driven Model Predictive Control
  ☆71Updated 2 years ago
• linesd / SSGPR
  Sparse Spectrum Gaussian Process Regression
  ☆24Updated 5 years ago
• decargroup / pykoop
  Koopman operator identification library in Python, compatible with `scikit-learn`
  ☆99Updated 2 months ago
• wuwushrek / physics_constrained_nn
  Neural Networks with Physics-Informed Architectures and Constraints for Dynamical Systems Modeling
  ☆53Updated 4 years ago
• lubaroli / dust
  This is the code repository for the DuSt-MPC paper, published at Robotics: Science and Systems (RSS) 2021.
  ☆28Updated 4 years ago
• Dynamic-Systems-and-GP / GPdyn
  Gaussian Process Model Dynamic System Identification Toolbox for Matlab
  ☆94Updated 8 years ago
• LemonPi / pytorch_cem
  Cross Entropy Method implemented in pytorch
  ☆37Updated 3 years ago
• thaipduong / SE3HamDL
  Code for our RSS'21 paper: "Hamiltonian-based Neural ODE Networks on the SE(3) Manifold For Dynamics Learning and Control"
  ☆47Updated 2 years ago
• Eric-Bradford / UKF-SNMPC
  This repository contains the source code for “Unscented Kalman filter stochastic nonlinear model predictive control” (UKF-SNMPC).
  ☆60Updated 2 years ago
• wjmaddox / online_vargp
  Online variational GPs
  ☆37Updated 2 years ago
• clegaard / deep_learning_for_dynamical_systems
  ☆89Updated 2 years ago