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.
  ☆57Updated 2 years ago
• wuwushrek / physics_constrained_nn
  Neural Networks with Physics-Informed Architectures and Constraints for Dynamical Systems Modeling
  ☆51Updated 3 years ago
• Physics-aware-AI / Symplectic-ODENet
  ☆45Updated 4 years ago
• TUM-ITR / koopcore
  Koopman Kernels for Learning Dynamical Systems from Trajectory Data
  ☆30Updated last year
• PredictiveIntelligenceLab / GP-NODEs
  ☆29Updated 2 years ago
• DrewSosa / dissipative_hnns
  Training neural networks to disentangle conservative and dissipative dynamics
  ☆10Updated 3 years ago
• GaloisInc / dlkoopman
  A general-purpose Python package for Koopman theory using deep learning.
  ☆106Updated 6 months ago
• yuan-yin / APHYNITY
  Augmenting Physical Models with Deep Networks for Complex Dynamics Forecasting
  ☆47Updated last year
• donken / NeuralOC
  A Neural Network Approach for Real-Time High-Dimensional Optimal Control
  ☆27Updated 2 years ago
• lukebhan / PDEControlGym
  This gym provides implementations of various PDEs for easy testing and comparison of data-driven and classical PDE control algorithms.
  ☆30Updated last month
• YunzhuLi / CompositionalKoopmanOperators
  [ICLR 2020] Learning Compositional Koopman Operators for Model-Based Control
  ☆90Updated 4 years ago
• DiffEqML / torchcontrol
  A PyTorch library for all things nonlinear control and reinforcement learning.
  ☆47Updated 3 years ago
• erichson / koopmanAE
  Consistent Koopman Autoencoders
  ☆74Updated 2 years ago
• sisl / variational_koopman
  Source code for "Deep Variational Koopman Models: Inferring Koopman Observations for Uncertainty-Aware Dynamics Modeling and Control" fro…
  ☆41Updated 6 years ago
• decargroup / pykoop
  Koopman operator identification library in Python, compatible with `scikit-learn`
  ☆85Updated last month
• nzolman / sindy-rl
  Code for "SINDy-RL: Interpretable and Efficient Model-Based Reinforcement Learning" by Zolman et al.
  ☆128Updated this week
• Machine-Learning-Dynamical-Systems / kooplearn
  A Python package to learn the Koopman operator.
  ☆61Updated 9 months ago
• EthanJamesLew / AutoKoopman
  AutoKoopman - automated Koopman operator methods for data-driven dynamical systems analysis and control.
  ☆78Updated last year
• xl402 / deep-koopman
  IIB Master's Project: Deep Learning for Koopman Optimal Predictive Control
  ☆47Updated 4 years ago
• BethanyL / DeepKoopman
  neural networks to learn Koopman eigenfunctions
  ☆422Updated last year
• zabaras / transformer-physx
  Transformers for modeling physical systems
  ☆143Updated 2 years ago
• sklus / d3s
  Data-driven dynamical systems toolbox.
  ☆74Updated 3 weeks ago
• clegaard / deep_learning_for_dynamical_systems
  ☆88Updated 2 years ago
• dynamicslab / hydrogym
  An RL-Gym for Challenge Problems in Data-Driven Modeling and Control of Fluid Dynamics.
  ☆75Updated last month
• coursekevin / svise
  Accompanying code for "State Estimation of a Physical System without Governing Equations"
  ☆89Updated last year
• dmusekamp / al4pde
  AL4PDE: A Benchmark for Active Learning for Neural PDE Solvers
  ☆27Updated 2 months ago
• mfinzi / constrained-hamiltonian-neural-networks
  ☆110Updated 4 years ago
• cagatayyildiz / npde
  Nonparametric Differential Equation Modeling
  ☆54Updated last year
• ivandariojr / LyapunovLearning
  ☆43Updated 2 years ago
• locuslab / stable_dynamics
  Companion code to "Learning Stable Deep Dynamics Models" (Manek and Kolter, 2019)
  ☆33Updated 5 years ago