Bigpig4396 / Incremental-Gaussian-Process-Regression-IGPRLinks
☆16Updated 3 years ago
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
Sorting:
- Official PyTorch implementation of "Deep State Space Models for Nonlinear System Identification", 2020.☆96Updated 3 years ago
- ☆15Updated 6 years ago
- Mixtures of Gaussian Process Experts in GPflow/TensorFlow☆11Updated 3 years ago
- ☆11Updated 7 years ago
- ☆24Updated 4 years ago
- Model-based Control using Koopman Operators☆51Updated 5 years ago
- [ICLR 2020] Learning Compositional Koopman Operators for Model-Based Control☆90Updated 4 years ago
- This repository contains the source code to perform Geometry-aware Bayesian Optimization (GaBO) on Riemannian manifolds.☆52Updated 3 years ago
- Source code for "Deep Variational Koopman Models: Inferring Koopman Observations for Uncertainty-Aware Dynamics Modeling and Control" fro…☆41Updated 6 years ago
- Companion code for RSS 2020 paper: "Active Preference-Based Gaussian Process Regression for Reward Learning"☆39Updated last year
- IIB Master's Project: Deep Learning for Koopman Optimal Predictive Control☆47Updated 4 years ago
- Streaming sparse Gaussian process approximations☆67Updated 2 years ago
- Differentiable predictive control (DPC) policy optimization examples.☆55Updated last year
- Repository for construction of Koopman eigenfunctions for unknown dynamical systems and identification of a lifted state-space model usin…☆27Updated 2 years ago
- A framework for neural network control of dynamical systems over graphs.☆57Updated 2 years ago
- Gaussian Process Model Dynamic System Identification Toolbox for Matlab☆94Updated 7 years ago
- Pytorch implementation of Model Predictive Control with learned models☆30Updated 4 years ago
- DyNODE: Neural Ordinary Differential Equations for Dynamics Modeling in Continuous Control☆23Updated 4 years ago
- Sparse Spectrum Gaussian Process Regression☆23Updated 5 years ago
- Neural Networks with Physics-Informed Architectures and Constraints for Dynamical Systems Modeling☆50Updated 3 years ago
- AutoKoopman - automated Koopman operator methods for data-driven dynamical systems analysis and control.☆76Updated last year
- Code for our RSS'21 paper: "Hamiltonian-based Neural ODE Networks on the SE(3) Manifold For Dynamics Learning and Control"☆44Updated 2 years ago
- Input Inference for Control (i2c), a control-as-inference framework for optimal control☆25Updated last year
- Automatic Tuning for Data-driven Model Predictive Control☆67Updated 2 years ago
- Enforcing robust control guarantees within neural network policies☆54Updated 4 years ago
- Stable Gaussian Process based Tracking Control of Euler-Lagrange Systems☆13Updated 5 years ago
- stochastic recursive Gaussian Process (SRGP)☆20Updated 4 years ago
- ☆88Updated 2 years ago
- Koopman Kernels for Learning Dynamical Systems from Trajectory Data☆29Updated last year
- Koopman operator identification library in Python, compatible with `scikit-learn`☆80Updated 3 weeks ago