mlpotter / DeepKoopmanLuschLinks
PyTorch Implementation of Lusch et al DeepKoopman
☆13Updated 2 years ago
Alternatives and similar repositories for DeepKoopmanLusch
Users that are interested in DeepKoopmanLusch are comparing it to the libraries listed below
Sorting:
- Source code for "Deep Variational Koopman Models: Inferring Koopman Observations for Uncertainty-Aware Dynamics Modeling and Control" fro…☆40Updated 6 years ago
- IIB Master's Project: Deep Learning for Koopman Optimal Predictive Control☆45Updated 4 years ago
- Consistent Koopman Autoencoders☆74Updated 2 years ago
- AutoKoopman - automated Koopman operator methods for data-driven dynamical systems analysis and control.☆73Updated last year
- Pytorch Implementation of Deep Kalman Filter☆9Updated 2 years ago
- Official PyTorch implementation of "Deep State Space Models for Nonlinear System Identification", 2020.☆92Updated 3 years ago
- A general-purpose Python package for Koopman theory using deep learning.☆104Updated 3 months ago
- Neural Networks with Physics-Informed Architectures and Constraints for Dynamical Systems Modeling☆48Updated 3 years ago
- Physics-informed Dyna-style model-based deep reinforcement learning for dynamic control☆54Updated 3 years ago
- Data-driven Koopman control theory applied to reinforcement learning!☆32Updated last year
- ☆72Updated 7 years ago
- Learning Koopman operator by EDMD with trainable dictionary☆25Updated 2 years ago
- Deep learning assisted dynamic mode decomposition☆19Updated 3 years ago
- Official implementation of "Physics-Informed Long-Sequence Forecasting From Multi-Resolution Spatiotemporal Data".☆10Updated 2 years ago
- Multifactor Sequential Disentanglement via Structured Koopman Autoencoders☆18Updated 6 months ago
- A framework for neural network control of dynamical systems over graphs.☆58Updated 2 years ago
- ☆22Updated 3 years ago
- A Python package to learn the Koopman operator.☆57Updated 6 months ago
- Neural Extended Kalman Filters☆14Updated last year
- Koopman Reduced-Order Nonlinear Identification and Control☆90Updated 5 years ago
- [Applied Energy] This work proposes an Input Convex LSTM neural network for real-time neural network-based optimization.☆15Updated last month
- ☆15Updated 4 years ago
- In this work, we present a novel approach that combines the power of Koopman operators and deep neural networks to generate a linear rep…☆10Updated 10 months ago
- Neural Laplace Control for Continuous-time Delayed Systems - an offline RL method combining Neural Laplace dynamics model and MPC planner…☆12Updated 2 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
- AI4Science: Efficient data-driven Online Model Learning (OML) / system identification and control☆30Updated 2 years ago
- ☆14Updated last year
- Augmenting Physical Models with Deep Networks for Complex Dynamics Forecasting☆46Updated last year
- ☆19Updated 5 years ago
- Use deep learning to learn Koopman operator and LQR for optimal control☆16Updated 4 years ago