Alternatives and similar repositories for koopmanAE

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

• helange23 / from_fourier_to_koopman
  Linear and non-linear spectral forecasting algorithms
  ☆138Updated 4 years ago
• JayLago / DLDMD
  Deep learning assisted dynamic mode decomposition
  ☆19Updated 4 years ago
• dgedon / DeepSSM_SysID
  Official PyTorch implementation of "Deep State Space Models for Nonlinear System Identification", 2020.
  ☆96Updated 3 years ago
• mlpotter / DeepKoopmanLusch
  PyTorch Implementation of Lusch et al DeepKoopman
  ☆14Updated 2 years ago
• pvlachas / RNN-Lyapunov-Spectrum
  A data-driven method to calculate the Lyapunov exponent of a dynamical system employing a GRU-RNN.
  ☆46Updated last year
• sisl / variational_koopman
  Source code for "Deep Variational Koopman Models: Inferring Koopman Observations for Uncertainty-Aware Dynamics Modeling and Control" fro…
  ☆42Updated 6 years ago
• clegaard / deep_learning_for_dynamical_systems
  ☆89Updated 2 years ago
• yuan-yin / APHYNITY
  Augmenting Physical Models with Deep Networks for Complex Dynamics Forecasting
  ☆47Updated last year
• BethanyL / DeepKoopman
  neural networks to learn Koopman eigenfunctions
  ☆430Updated last year
• Machine-Learning-Dynamical-Systems / kooplearn
  A Python package to learn the Koopman operator.
  ☆61Updated this week
• mlech26l / ode-lstms
  Code repository of the paper Learning Long-Term Dependencies in Irregularly-Sampled Time Series
  ☆119Updated 2 years ago
• zabaras / transformer-physx
  Transformers for modeling physical systems
  ☆144Updated 2 years ago
• Physics-aware-AI / Symplectic-ODENet
  ☆47Updated 4 years ago
• yongkyung-oh / Stable-Neural-SDEs
  [ICLR 2024] Stable Neural Stochastic Differential Equations in Analyzing Irregular Time Series Data
  ☆52Updated last month
• sungyongs / dpgn
  Differentiable Physics-informed Graph Networks
  ☆67Updated 5 years ago
• PredictiveIntelligenceLab / GP-NODEs
  ☆28Updated 2 years ago
• n-takeishi / learning-kis
  Demo implementation of Learning Koopman Invariant Subspaces for Dynamic Mode Decomposition
  ☆40Updated 3 years ago
• d-biswa / Symplectic-ODENet
  ☆15Updated 4 years ago
• GaloisInc / dlkoopman
  A general-purpose Python package for Koopman theory using deep learning.
  ☆108Updated 2 weeks ago
• wuwushrek / physics_constrained_nn
  Neural Networks with Physics-Informed Architectures and Constraints for Dynamical Systems Modeling
  ☆52Updated 3 years ago
• Koopman-Laboratory / KoopmanLab
  A library for Koopman Neural Operator with Pytorch.
  ☆303Updated last year
• tonyduan / mixture-density-network
  Mixture density network implemented in PyTorch.
  ☆150Updated 2 years ago
• loiseaujc / SINDy
  ☆41Updated 7 years ago
• asikist / nnc
  A framework for neural network control of dynamical systems over graphs.
  ☆56Updated 3 years ago
• JRice15 / physics-informed-autoencoders
  Code for Rice et al. 2020 "Analyzing Koopman approaches to physics-informed machine learning for long-term sea-surface temperature forcea…
  ☆36Updated last month
• crispitagorico / torchspde
  Neural Stochastic PDEs: resolution-invariant modelling of continuous spatiotemporal dynamics
  ☆53Updated 2 years ago
• yriyazi / Koopman-Operator-and-Deep-Neural-Networks-ISAV2023
  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 last year
• pvlachas / RNN-RC-Chaos
  RNN architectures trained with Backpropagation and Reservoir Computing (RC) methods for forecasting high-dimensional chaotic dynamical sy…
  ☆96Updated 2 years ago
• josephbakarji / deep-delay-autoencoder
  Discovers high dimensional models from 1D data using deep delay autoencoders
  ☆37Updated 2 years ago
• sklus / d3s
  Data-driven dynamical systems toolbox.
  ☆76Updated 2 months ago