Alternatives and similar repositories for datafold

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

• kpchamp / MultiscaleDiscovery
  ☆30Updated 7 years ago
• loiseaujc / SINDy
  ☆41Updated 7 years ago
• katiana22 / GDM-PCE
  Source code of: "Manifold learning-based polynomial chaos expansions for high-dimensional surrogate models".
  ☆37Updated 3 years ago
• PredictiveIntelligenceLab / BayesianDifferentiableProgramming
  ☆21Updated 5 years ago
• niallmm / iSINDy
  implicit-SINDy code example from paper "Inferring Biological Networks by Sparse Identification fo Nonlinear Dynamics" http://ieeexplore.i…
  ☆30Updated 8 years ago
• Ohjeah / sparsereg
  a collection of modern sparse (regularized) linear regression algorithms.
  ☆65Updated 5 years ago
• cagatayyildiz / npode
  Learning unknown ODE models with Gaussian processes
  ☆26Updated 7 years ago
• PredictiveIntelligenceLab / GP-NODEs
  ☆28Updated 2 years ago
• arbabiha / StochasticModelingwData
  Data-driven modeling of chaotic systems in the form of SDEs and nonlinear observation maps
  ☆19Updated 5 years ago
• n-takeishi / bayesiandmd
  Bayesian Dynamic Mode Decomposition (Bayesian DMD)
  ☆18Updated 3 years ago
• TUM-ITR / koopcore
  Koopman Kernels for Learning Dynamical Systems from Trajectory Data
  ☆31Updated last year
• erichson / koopmanAE
  Consistent Koopman Autoencoders
  ☆74Updated 2 years ago
• mbudisic / koopman
  Koopman Mode Decomposition
  ☆73Updated 8 years ago
• pswpswpsw / SKDMD
  Sparsity-promoting Kernel Dynamic Mode Decomposition for Nonlinear Dynamical Systems
  ☆30Updated 3 years ago
• sklus / d3s
  Data-driven dynamical systems toolbox.
  ☆76Updated 2 months 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…
  ☆21Updated 2 years ago
• luckystarufo / pySINDy
  SINDy (Sparse Identification of Nonlinear Dynamics) algorithms
  ☆79Updated 2 years ago
• cselab / LED
  ☆21Updated 2 years ago
• erichson / DMDpack
  Dynamic Mode Decomposition
  ☆60Updated 8 years ago
• maziarraissi / MultistepNNs
  Multistep Neural Networks for Data-driven Discovery of Nonlinear Dynamical Systems
  ☆63Updated 5 years ago
• AlexTMallen / koopman-forecasting
  Long-term probabilistic forecasting of quasiperiodic phenomena using Koopman theory
  ☆35Updated 3 years ago
• sayin / Data_Driven_Symbolic_Regression
  Interpretable machine learning (symbolic regression) using Genetic programming/Gene expression programming and Sparse regression used …
  ☆34Updated 4 years ago
• urban-fasel / SEIR_SINDY_MPC
  ☆45Updated 4 years ago
• dynamicslab / modified-SINDy
  Example code for paper: Automatic Differentiation to Simultaneously Identify Nonlinear Dynamics and Extract Noise Probability Distributio…
  ☆57Updated 3 years ago
• n-takeishi / learning-kis
  Demo implementation of Learning Koopman Invariant Subspaces for Dynamic Mode Decomposition
  ☆40Updated 3 years ago
• briandesilva / discovery-of-physics-from-data
  Code to accompany the paper "Discovery of Physics from Data: Universal Laws and Discrepancies"
  ☆28Updated 5 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
• dynamicslab / SINDy-PI
  SINDy-PI: A Robust Algorithm for Parallel Implicit Sparse Identification of Nonlinear Dynamics
  ☆153Updated 4 years ago
• HwijaeSon / AL-PINNs
  Official code for AL-PINNS: Augmented Lagrangian relaxation method for Physics-Informed Neural Networks
  ☆10Updated 2 years ago
• helange23 / from_fourier_to_koopman
  Linear and non-linear spectral forecasting algorithms
  ☆138Updated 4 years ago