Alternatives and similar repositories for variational_koopman

Users that are interested in variational_koopman are comparing it to the libraries listed below

• xl402 / deep-koopman
  IIB Master's Project: Deep Learning for Koopman Optimal Predictive Control
  ☆45Updated 4 years ago
• erichson / koopmanAE
  Consistent Koopman Autoencoders
  ☆74Updated 2 years ago
• mlpotter / DeepKoopmanLusch
  PyTorch Implementation of Lusch et al DeepKoopman
  ☆13Updated 2 years ago
• LeeLinJun / KoopmanControl
  ☆19Updated 5 years ago
• morim3 / DeepKalmanFilter
  Pytorch Implementation of Deep Kalman Filter
  ☆9Updated 2 years ago
• locuslab / stable_dynamics
  Companion code to "Learning Stable Deep Dynamics Models" (Manek and Kolter, 2019)
  ☆33Updated 5 years ago
• Pdbz199 / Koopman-RL-Old
  Data-driven Koopman control theory applied to reinforcement learning!
  ☆32Updated last year
• ManshaP / KoopmanNets
  project for my essay on how to use neural networks to linearise nonlinear dynamical systems
  ☆9Updated 4 years ago
• YunzhuLi / CompositionalKoopmanOperators
  [ICLR 2020] Learning Compositional Koopman Operators for Model-Based Control
  ☆90Updated 4 years ago
• i-abr / mpc-koopman
  Model-based Control using Koopman Operators
  ☆51Updated 4 years ago
• tony23545 / DeepKoopman
  Use deep learning to learn Koopman operator and LQR for optimal control
  ☆16Updated 4 years ago
• wuwushrek / physics_constrained_nn
  Neural Networks with Physics-Informed Architectures and Constraints for Dynamical Systems Modeling
  ☆48Updated 3 years ago
• samholt / NeuralLaplaceControl
  Neural Laplace Control for Continuous-time Delayed Systems - an offline RL method combining Neural Laplace dynamics model and MPC planner…
  ☆12Updated 2 years ago
• MilanKorda / KoopmanMPC
  ☆72Updated 7 years ago
• i-abr / TorchMPC
  Pytorch implementation of Model Predictive Control with learned models
  ☆30Updated 4 years ago
• EthanJamesLew / AutoKoopman
  AutoKoopman - automated Koopman operator methods for data-driven dynamical systems analysis and control.
  ☆73Updated last year
• Cafolkes / keedmd
  Repository for construction of Koopman eigenfunctions for unknown dynamical systems and identification of a lifted state-space model usin…
  ☆28Updated 2 years ago
• cagatayyildiz / oderl
  Experiment code for "Continuous-Time Model-Based Reinforcement Learning"
  ☆53Updated last year
• dgedon / DeepSSM_SysID
  Official PyTorch implementation of "Deep State Space Models for Nonlinear System Identification", 2020.
  ☆92Updated 3 years ago
• asikist / nnc
  A framework for neural network control of dynamical systems over graphs.
  ☆58Updated 2 years ago
• Pdbz199 / koopman-rl
  High-quality single file implementation of Deep Reinforcement Learning algorithms with research-friendly features (PPO, DQN, C51, DDPG, T…
  ☆13Updated 4 months ago
• d-biswa / Symplectic-ODENet
  ☆15Updated 4 years ago
• vmartinezalvarez / DyNODE
  DyNODE: Neural Ordinary Differential Equations for Dynamics Modeling in Continuous Control
  ☆23Updated 4 years ago
• DesmondZhong / Lagrangian_caVAE
  Official implementation for our paper "Unsupervised Learning of Lagrangian Dynamics from Images for Prediction and Control"
  ☆19Updated 2 years ago
• chennnnnyize-zz / Optimal-Control-via-Neural-Networks
  Code repo for ICLR paper: Optimal Control Via Neural Networks: A Convex Approach
  ☆83Updated 6 years ago
• donken / NeuralOC
  A Neural Network Approach for Real-Time High-Dimensional Optimal Control
  ☆26Updated 2 years ago
• giorgosmamakoukas / MemoryEfficientStableLDS
  Codebase associated with paper "Memory-Efficient Learning of Stable Linear Dynamical Systems for Prediction and Control"
  ☆24Updated 4 years ago
• Physics-aware-AI / Symplectic-ODENet
  ☆45Updated 4 years ago
• i-abr / active-learning-koopman
  ☆24Updated 4 years ago
• yuan-yin / APHYNITY
  Augmenting Physical Models with Deep Networks for Complex Dynamics Forecasting
  ☆46Updated last year