YunzhuLi / CompositionalKoopmanOperatorsLinks
[ICLR 2020] Learning Compositional Koopman Operators for Model-Based Control
☆90Updated 4 years ago
Alternatives and similar repositories for CompositionalKoopmanOperators
Users that are interested in CompositionalKoopmanOperators are comparing it to the libraries listed below
Sorting:
- IIB Master's Project: Deep Learning for Koopman Optimal Predictive Control☆46Updated 4 years ago
- Source code for "Deep Variational Koopman Models: Inferring Koopman Observations for Uncertainty-Aware Dynamics Modeling and Control" fro…☆40Updated 6 years ago
- Model-based Control using Koopman Operators☆51Updated 5 years ago
- Companion code to "Learning Stable Deep Dynamics Models" (Manek and Kolter, 2019)☆33Updated 5 years ago
- ☆19Updated 5 years ago
- DyNODE: Neural Ordinary Differential Equations for Dynamics Modeling in Continuous Control☆23Updated 4 years ago
- Repository for construction of Koopman eigenfunctions for unknown dynamical systems and identification of a lifted state-space model usin…☆28Updated 2 years ago
- Neural Networks with Physics-Informed Architectures and Constraints for Dynamical Systems Modeling☆48Updated 3 years ago
- A framework for neural network control of dynamical systems over graphs.☆57Updated 2 years ago
- ☆21Updated 6 years ago
- project for my essay on how to use neural networks to linearise nonlinear dynamical systems☆9Updated 4 years ago
- Input Inference for Control (i2c), a control-as-inference framework for optimal control☆25Updated last year
- Use deep learning to learn Koopman operator and LQR for optimal control☆16Updated 4 years ago
- Learning Lyapunov functions and control policies of nonlinear dynamical systems☆134Updated 4 years ago
- ☆45Updated 4 years ago
- Koopman Kernels for Learning Dynamical Systems from Trajectory Data☆27Updated last year
- Consistent Koopman Autoencoders☆74Updated 2 years ago
- This repository contains the source code to perform Geometry-aware Bayesian Optimization (GaBO) on Riemannian manifolds.☆52Updated 3 years ago
- Data-driven Koopman control theory applied to reinforcement learning!☆32Updated last year
- ☆73Updated 4 years ago
- Official implementation for our paper "Unsupervised Learning of Lagrangian Dynamics from Images for Prediction and Control"☆19Updated 2 years ago
- Enforcing robust control guarantees within neural network policies☆53Updated 4 years ago
- A Neural Network Approach for Real-Time High-Dimensional Optimal Control☆26Updated 2 years ago
- Pytorch implementation of Model Predictive Control with learned models☆30Updated 4 years ago
- ☆72Updated 7 years ago
- ☆24Updated 4 years ago
- Companion code for RSS 2020 paper: "Active Preference-Based Gaussian Process Regression for Reward Learning"☆39Updated last year
- Demo implementation of Learning Koopman Invariant Subspaces for Dynamic Mode Decomposition☆40Updated 3 years ago
- High-quality single file implementation of Deep Reinforcement Learning algorithms with research-friendly features (PPO, DQN, C51, DDPG, T…☆13Updated 4 months ago
- By introducing a differentiable contact model, DiffCoSim extends the applicability of Lagrangian/Hamiltonian-inspired neural networks to …☆36Updated 2 years ago