Alternatives and similar repositories for nnc

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

• xl402 / deep-koopman
  IIB Master's Project: Deep Learning for Koopman Optimal Predictive Control
  ☆49Updated 5 years ago
• wuwushrek / physics_constrained_nn
  Neural Networks with Physics-Informed Architectures and Constraints for Dynamical Systems Modeling
  ☆52Updated 4 years ago
• donken / NeuralOC
  A Neural Network Approach for Real-Time High-Dimensional Optimal Control
  ☆27Updated 3 years ago
• EthanJamesLew / AutoKoopman
  AutoKoopman - automated Koopman operator methods for data-driven dynamical systems analysis and control.
  ☆79Updated last year
• sklus / d3s
  Data-driven dynamical systems toolbox.
  ☆77Updated 3 weeks ago
• YunzhuLi / CompositionalKoopmanOperators
  [ICLR 2020] Learning Compositional Koopman Operators for Model-Based Control
  ☆91Updated 4 years ago
• sisl / variational_koopman
  Source code for "Deep Variational Koopman Models: Inferring Koopman Observations for Uncertainty-Aware Dynamics Modeling and Control" fro…
  ☆43Updated 6 years ago
• locuslab / stable_dynamics
  Companion code to "Learning Stable Deep Dynamics Models" (Manek and Kolter, 2019)
  ☆33Updated 5 years ago
• Physics-aware-AI / Symplectic-ODENet
  ☆47Updated 4 years ago
• d-biswa / Symplectic-ODENet
  ☆15Updated 4 years ago
• eurika-kaiser / KRONIC
  Koopman Reduced-Order Nonlinear Identification and Control
  ☆92Updated 5 years ago
• Machine-Learning-Dynamical-Systems / kooplearn
  A Python package to learn the Koopman operator.
  ☆63Updated last week
• GaloisInc / dlkoopman
  A general-purpose Python package for Koopman theory using deep learning.
  ☆115Updated last month
• dgedon / DeepSSM_SysID
  Official PyTorch implementation of "Deep State Space Models for Nonlinear System Identification", 2020.
  ☆98Updated 3 years ago
• TUM-ITR / koopcore
  Koopman Kernels for Learning Dynamical Systems from Trajectory Data
  ☆31Updated last year
• Pdbz199 / Koopman-RL-Old
  Data-driven Koopman control theory applied to reinforcement learning!
  ☆34Updated 2 years ago
• 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
• clegaard / deep_learning_for_dynamical_systems
  ☆89Updated 2 years ago
• chennnnnyize-zz / Optimal-Control-via-Neural-Networks
  Code repo for ICLR paper: Optimal Control Via Neural Networks: A Convex Approach
  ☆84Updated 6 years ago
• JoeMWatson / input-inference-for-control
  Input Inference for Control (i2c), a control-as-inference framework for optimal control
  ☆25Updated 2 years ago
• DiffEqML / torchcontrol
  A PyTorch library for all things nonlinear control and reinforcement learning.
  ☆47Updated 4 years ago
• locuslab / robust-nn-control
  Enforcing robust control guarantees within neural network policies
  ☆55Updated 4 years ago
• pnnl / deps_arXiv2020
  Differentiable predictive control (DPC) policy optimization examples.
  ☆59Updated 2 years ago
• decargroup / pykoop
  Koopman operator identification library in Python, compatible with `scikit-learn`
  ☆98Updated last month
• i-abr / mpc-koopman
  Model-based Control using Koopman Operators
  ☆55Updated 5 years ago
• StanfordASL / Adaptive-Control-Oriented-Meta-Learning
  Adaptive control-oriented meta-learning for nonlinear systems
  ☆69Updated 4 years ago
• YaChienChang / Neural-Lyapunov-Control
  Learning Lyapunov functions and control policies of nonlinear dynamical systems
  ☆138Updated 4 years ago
• IlyaOrson / Control-NeuralODE
  Neural ODEs as Feedback Policies for Nonlinear Optimal Control (IFAC 2023) https://doi.org/10.1016/j.ifacol.2023.10.1248
  ☆18Updated 2 years ago
• cagatayyildiz / npode
  Learning unknown ODE models with Gaussian processes
  ☆27Updated 7 years ago
• forgi86 / dynonet
  "dynoNet: A neural network architecture for learning dynamical systems" by Marco Forgione and Dario Piga
  ☆48Updated last year