asikist / nncLinks
A framework for neural network control of dynamical systems over graphs.
☆56Updated 3 years ago
Alternatives and similar repositories for nnc
Users that are interested in nnc are comparing it to the libraries listed below
Sorting:
- IIB Master's Project: Deep Learning for Koopman Optimal Predictive Control☆50Updated 5 years ago
- A Neural Network Approach for Real-Time High-Dimensional Optimal Control☆27Updated 3 years ago
- Neural Networks with Physics-Informed Architectures and Constraints for Dynamical Systems Modeling☆53Updated 4 years ago
- Source code for "Deep Variational Koopman Models: Inferring Koopman Observations for Uncertainty-Aware Dynamics Modeling and Control" fro…☆43Updated 6 years ago
- AutoKoopman - automated Koopman operator methods for data-driven dynamical systems analysis and control.☆81Updated last year
- Koopman Kernels for Learning Dynamical Systems from Trajectory Data☆31Updated 2 years ago
- Data-driven dynamical systems toolbox.☆78Updated last month
- [ICLR 2020] Learning Compositional Koopman Operators for Model-Based Control☆93Updated 4 years ago
- Companion code to "Learning Stable Deep Dynamics Models" (Manek and Kolter, 2019)☆33Updated 6 years ago
- Repository for construction of Koopman eigenfunctions for unknown dynamical systems and identification of a lifted state-space model usin…☆29Updated 3 years ago
- Data-driven Koopman control theory applied to reinforcement learning!☆34Updated 2 years ago
- ☆46Updated 4 years ago
- ☆15Updated 4 years ago
- Koopman Reduced-Order Nonlinear Identification and Control☆92Updated 5 years ago
- A PyTorch library for all things nonlinear control and reinforcement learning.☆47Updated 4 years ago
- A Python package to learn the Koopman operator.☆63Updated last week
- Koopman operator identification library in Python, compatible with `scikit-learn`☆99Updated 2 months ago
- ☆89Updated 2 years ago
- DyNODE: Neural Ordinary Differential Equations for Dynamics Modeling in Continuous Control☆23Updated 5 years ago
- Official PyTorch implementation of "Deep State Space Models for Nonlinear System Identification", 2020.☆99Updated 3 years ago
- Code repo for ICLR paper: Optimal Control Via Neural Networks: A Convex Approach☆84Updated 6 years ago
- Model-based Control using Koopman Operators☆57Updated 5 years ago
- ☆78Updated 7 years ago
- Differentiable predictive control (DPC) policy optimization examples.☆61Updated 2 years ago
- A general-purpose Python package for Koopman theory using deep learning.☆116Updated 2 months ago
- Code for "Learning Control-Oriented Dynamical Structure from Data" by Spencer M. Richards, Jean-Jacques Slotine, Navid Azizan, and Marco …☆22Updated 2 years ago
- Enforcing robust control guarantees within neural network policies☆55Updated 4 years ago
- Use deep learning to learn Koopman operator and LQR for optimal control☆16Updated 5 years ago
- Input Inference for Control (i2c), a control-as-inference framework for optimal control☆25Updated 2 years ago
- Codebase associated with paper "Memory-Efficient Learning of Stable Linear Dynamical Systems for Prediction and Control"☆24Updated 5 years ago