Alternatives and similar repositories for Symplectic-ODENet

Users that are interested in Symplectic-ODENet are comparing it to the libraries listed below

• asikist / nnc
  A framework for neural network control of dynamical systems over graphs.
  ☆56Updated 3 years ago
• Physics-aware-AI / Symplectic-ODENet
  ☆47Updated 4 years ago
• wuwushrek / physics_constrained_nn
  Neural Networks with Physics-Informed Architectures and Constraints for Dynamical Systems Modeling
  ☆52Updated 4 years ago
• PredictiveIntelligenceLab / GP-NODEs
  ☆28Updated 3 years ago
• DrewSosa / dissipative_hnns
  Training neural networks to disentangle conservative and dissipative dynamics
  ☆10Updated 3 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
• yuan-yin / APHYNITY
  Augmenting Physical Models with Deep Networks for Complex Dynamics Forecasting
  ☆48Updated last year
• erichson / koopmanAE
  Consistent Koopman Autoencoders
  ☆74Updated 2 years ago
• donken / NeuralOC
  A Neural Network Approach for Real-Time High-Dimensional Optimal Control
  ☆27Updated 3 years ago
• Machine-Learning-Dynamical-Systems / kooplearn
  A Python package to learn the Koopman operator.
  ☆63Updated this week
• xl402 / deep-koopman
  IIB Master's Project: Deep Learning for Koopman Optimal Predictive Control
  ☆49Updated 5 years ago
• DiffEqML / torchcontrol
  A PyTorch library for all things nonlinear control and reinforcement learning.
  ☆47Updated 4 years ago
• lukebhan / PDEControlGym
  This gym provides implementations of various PDEs for easy testing and comparison of data-driven and classical PDE control algorithms.
  ☆34Updated 4 months ago
• TUM-ITR / koopcore
  Koopman Kernels for Learning Dynamical Systems from Trajectory Data
  ☆31Updated last year
• EthanJamesLew / AutoKoopman
  AutoKoopman - automated Koopman operator methods for data-driven dynamical systems analysis and control.
  ☆79Updated last year
• YunzhuLi / CompositionalKoopmanOperators
  [ICLR 2020] Learning Compositional Koopman Operators for Model-Based Control
  ☆91Updated 4 years ago
• GaloisInc / dlkoopman
  A general-purpose Python package for Koopman theory using deep learning.
  ☆115Updated last month
• dmusekamp / al4pde
  AL4PDE: A Benchmark for Active Learning for Neural PDE Solvers
  ☆29Updated 5 months 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
• sklus / d3s
  Data-driven dynamical systems toolbox.
  ☆77Updated 3 weeks ago
• locuslab / stable_dynamics
  Companion code to "Learning Stable Deep Dynamics Models" (Manek and Kolter, 2019)
  ☆33Updated 5 years ago
• fusion-ml / OCBO
  Offline Contextual Bayesian Optimization
  ☆14Updated 2 years ago
• clegaard / deep_learning_for_dynamical_systems
  ☆89Updated 2 years ago
• nzolman / sindy-rl
  Code for "SINDy-RL: Interpretable and Efficient Model-Based Reinforcement Learning" by Zolman et al.
  ☆142Updated 2 months ago
• vmartinezalvarez / DyNODE
  DyNODE: Neural Ordinary Differential Equations for Dynamics Modeling in Continuous Control
  ☆23Updated 5 years ago
• BethanyL / DeepKoopman
  neural networks to learn Koopman eigenfunctions
  ☆442Updated last year
• DesmondZhong / Lagrangian_caVAE
  Official implementation for our paper "Unsupervised Learning of Lagrangian Dynamics from Images for Prediction and Control"
  ☆20Updated 3 years ago
• pnnl / NeuralDAEs
  Learning Neural Differential Algebraic Equations via Operator Splitting
  ☆21Updated 3 months ago
• mfinzi / constrained-hamiltonian-neural-networks
  ☆112Updated 4 years ago
• ivandariojr / LyapunovLearning
  ☆44Updated 2 years ago