samholt / NeuralLaplaceControl
Neural Laplace Control for Continuous-time Delayed Systems - an offline RL method combining Neural Laplace dynamics model and MPC planner to achieve near-expert policy performance in environments with irregular time intervals and an unknown constant delay.
☆11Updated last year
Alternatives and similar repositories for NeuralLaplaceControl:
Users that are interested in NeuralLaplaceControl are comparing it to the libraries listed below
- Source code for "Deep Variational Koopman Models: Inferring Koopman Observations for Uncertainty-Aware Dynamics Modeling and Control" fro…☆37Updated 5 years ago
- IIB Master's Project: Deep Learning for Koopman Optimal Predictive Control☆45Updated 4 years ago
- Use deep learning to learn Koopman operator and LQR for optimal control☆16Updated 4 years ago
- AutoKoopman - automated Koopman operator methods for data-driven dynamical systems analysis and control.☆69Updated 9 months ago
- Experiment code for "Continuous-Time Model-Based Reinforcement Learning"☆50Updated last year
- Koopman Kernels for Learning Dynamical Systems from Trajectory Data☆24Updated last year
- A Neural Network Approach for Real-Time High-Dimensional Optimal Control☆26Updated 2 years ago
- Data-driven Koopman control theory applied to reinforcement learning!☆30Updated last year
- Code for the paper, "Industrial, large-scale model predictive control with structured neural networks."☆17Updated 3 years ago
- Pytorch Implementation of Deep Kalman Filter☆9Updated 2 years ago
- Consistent Koopman Autoencoders☆71Updated last year
- Companion code to "Learning Stable Deep Dynamics Models" (Manek and Kolter, 2019)☆32Updated 5 years ago
- Model-based Control using Koopman Operators☆51Updated 4 years ago
- ☆16Updated 4 years ago
- Official implementation for our paper "Unsupervised Learning of Lagrangian Dynamics from Images for Prediction and Control"☆18Updated 2 years ago
- AI4Science: Efficient data-driven Online Model Learning (OML) / system identification and control☆30Updated 2 years ago
- ☆66Updated 6 years ago
- project for my essay on how to use neural networks to linearise nonlinear dynamical systems☆9Updated 4 years ago
- A PyTorch library for all things nonlinear control and reinforcement learning.☆45Updated 3 years ago
- Pytorch implementation of Model Predictive Control with learned models☆30Updated 4 years ago
- ☆14Updated 6 years ago
- DyNODE: Neural Ordinary Differential Equations for Dynamics Modeling in Continuous Control☆22Updated 4 years ago
- This repository contains the source code for "Stochastic data-driven model predictive control using Gaussian processes" (SDD-GP-MPC).☆50Updated last year
- [ICLR 2020] Learning Compositional Koopman Operators for Model-Based Control☆88Updated 3 years ago
- Unofficial Implementation of the paper "Data-Efficient Reinforcement Learning with Probabilistic Model Predictive Control", applied to gy…☆134Updated last year
- ☆13Updated last year
- High-quality single file implementation of Deep Reinforcement Learning algorithms with research-friendly features (PPO, DQN, C51, DDPG, T…☆11Updated last month
- Repository for Koopman based learning and nonlinear control☆39Updated 2 years ago
- Codebase associated with paper "Memory-Efficient Learning of Stable Linear Dynamical Systems for Prediction and Control"☆22Updated 4 years ago