TUM-ITR / koopcore
Koopman Kernels for Learning Dynamical Systems from Trajectory Data
☆26Updated last year
Alternatives and similar repositories for koopcore:
Users that are interested in koopcore are comparing it to the libraries listed below
- A Python package to learn the Koopman operator.☆56Updated 5 months ago
- DyNODE: Neural Ordinary Differential Equations for Dynamics Modeling in Continuous Control☆23Updated 4 years ago
- ☆29Updated 2 years ago
- A framework for neural network control of dynamical systems over graphs.☆58Updated 2 years ago
- IIB Master's Project: Deep Learning for Koopman Optimal Predictive Control☆45Updated 4 years ago
- Official implementation for our paper "Unsupervised Learning of Lagrangian Dynamics from Images for Prediction and Control"☆18Updated 2 years ago
- Implementation of the work Variational multiple shooting for Bayesian ODEs with Gaussian processes☆12Updated 2 years ago
- A Neural Network Approach for Real-Time High-Dimensional Optimal Control☆26Updated 2 years ago
- A PyTorch library for all things nonlinear control and reinforcement learning.☆46Updated 3 years ago
- Koopman operator identification library in Python, compatible with `scikit-learn`☆74Updated 5 months ago
- Data-driven dynamical systems toolbox.☆74Updated this week
- Neural Networks with Physics-Informed Architectures and Constraints for Dynamical Systems Modeling☆48Updated 3 years ago
- ☆15Updated 4 years ago
- Nonparametric Differential Equation Modeling☆53Updated last year
- AutoKoopman - automated Koopman operator methods for data-driven dynamical systems analysis and control.☆73Updated 11 months ago
- Source code for "Deep Variational Koopman Models: Inferring Koopman Observations for Uncertainty-Aware Dynamics Modeling and Control" fro…☆39Updated 5 years ago
- Companion code to "Learning Stable Deep Dynamics Models" (Manek and Kolter, 2019)☆33Updated 5 years ago
- By introducing a differentiable contact model, DiffCoSim extends the applicability of Lagrangian/Hamiltonian-inspired neural networks to …☆35Updated 2 years ago
- Online variational GPs☆33Updated last year
- Neural Laplace Control for Continuous-time Delayed Systems - an offline RL method combining Neural Laplace dynamics model and MPC planner…☆12Updated 2 years ago
- Neural ODEs as Feedback Policies for Nonlinear Optimal Control (IFAC 2023) https://doi.org/10.1016/j.ifacol.2023.10.1248☆16Updated last year
- Example code for paper: Automatic Differentiation to Simultaneously Identify Nonlinear Dynamics and Extract Noise Probability Distributio…☆54Updated 2 years ago
- Augmenting Physical Models with Deep Networks for Complex Dynamics Forecasting☆45Updated last year
- Uncertainty sets for nonlinear dynamical systems☆10Updated 4 years ago
- Learning unknown ODE models with Gaussian processes☆26Updated 6 years ago
- ☆19Updated last year
- Consistent Koopman Autoencoders☆74Updated last year
- This repository contains the source code to perform Geometry-aware Bayesian Optimization (GaBO) on Riemannian manifolds.☆51Updated 3 years ago
- Code for "Learning Control-Oriented Dynamical Structure from Data" by Spencer M. Richards, Jean-Jacques Slotine, Navid Azizan, and Marco …☆15Updated last year
- ☆40Updated last year