Alternatives and similar repositories for NystromKoopman:

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

• Machine-Learning-Dynamical-Systems / kooplearn
  A Python package to learn the Koopman operator.
  ☆53Updated 3 months ago
• j-wilson / GPflowSampling
  Code for efficiently sampling functions from GP(flow) posteriors
  ☆70Updated 4 years ago
• hegdepashupati / gaussian-process-odes
  Implementation of the work Variational multiple shooting for Bayesian ODEs with Gaussian processes
  ☆12Updated 2 years ago
• PredictiveIntelligenceLab / GP-NODEs
  ☆28Updated 2 years ago
• cagatayyildiz / npde
  Nonparametric Differential Equation Modeling
  ☆53Updated last year
• cagatayyildiz / npode
  Learning unknown ODE models with Gaussian processes
  ☆26Updated 6 years ago
• cagrell / gp_constr
  Python model for constrained GP
  ☆24Updated 3 years ago
• AaltoML / scalable-inference-in-sdes
  Methods and experiments for assumed density SDE approximations
  ☆11Updated 3 years ago
• erichson / koopmanAE
  Consistent Koopman Autoencoders
  ☆71Updated last year
• sdascoli / odeformer
  ☆60Updated 6 months ago
• sklus / d3s
  Data-driven dynamical systems toolbox.
  ☆73Updated 3 weeks ago
• wzhi / ODElearning_INN
  [ICML 2022] Learning Efficient and Robust Ordinary Differential \\ Equations via Invertible Neural Networks
  ☆10Updated last year
• gatsby-sahani / gp-sde
  ☆13Updated last year
• TUM-ITR / koopcore
  Koopman Kernels for Learning Dynamical Systems from Trajectory Data
  ☆24Updated last year
• arbabiha / StochasticModelingwData
  Data-driven modeling of chaotic systems in the form of SDEs and nonlinear observation maps
  ☆18Updated 4 years ago
• baddoo / LANDO
  Codes for Linear and Nonlinear Disambiguation Optimization (LANDO)
  ☆28Updated 3 years ago
• MatthieuDarcy / KernelFlows
  ☆12Updated 2 years ago
• crisbodnar / ndp
  Official code for the ICLR 2021 paper Neural ODE Processes
  ☆71Updated 2 years ago
• william-redman / Koopman-Neural-Network-Training
  Software to train neural networks via Koopman operator theory (see Dogra and Redman "Optimizing Neural Networks via Koopman Operator Theo…
  ☆19Updated last year
• kpchamp / MultiscaleDiscovery
  ☆27Updated 6 years ago
• tksmatsubara / symplectic-adjoint-method
  Code for "Symplectic Adjoint Method for Exact Gradient of Neural ODE with Minimal Memory," NeurIPS, 2021.
  ☆16Updated 3 years ago
• boschresearch / numerics_independent_neural_odes
  Code accompanying the ICLR 2021 paper "ResNet After All? Neural ODEs and Their Numerical Solution"
  ☆9Updated 2 years ago
• dynamicslab / modified-SINDy
  Example code for paper: Automatic Differentiation to Simultaneously Identify Nonlinear Dynamics and Extract Noise Probability Distributio…
  ☆54Updated 2 years ago
• a-norcliffe / sonode
  Experiments from the paper "On Second Order Behaviour in Augmented Neural ODEs"
  ☆57Updated 5 months ago
• niallmm / Hybrid-SINDy
  Sparse Identification of Nonlinear Dynamics for Hybrid Systems
  ☆23Updated 6 years ago
• NickGeneva / blog-code
  Code and files related to random side projects
  ☆21Updated 3 years ago
• dmusekamp / al4pde
  AL4PDE: A Benchmark for Active Learning for Neural PDE Solvers
  ☆18Updated last week
• asikist / nnc
  A framework for neural network control of dynamical systems over graphs.
  ☆57Updated 2 years ago
• crispitagorico / sigkernel
  Differentiable computations for the signature-PDE-kernel on CPU and GPU.
  ☆53Updated 9 months ago
• josephbakarji / deep-delay-autoencoder
  Discovers high dimensional models from 1D data using deep delay autoencoders
  ☆32Updated 2 years ago