Alternatives and similar repositories for data-assisted:

Users that are interested in data-assisted are comparing it to the libraries listed below

• maziarraissi / MultistepNNs
  Multistep Neural Networks for Data-driven Discovery of Nonlinear Dynamical Systems
  ☆63Updated 5 years ago
• niallmm / SINDy_AIC
  combination of sparse identification of nonlinear dynamics with Akaike information criteria
  ☆16Updated 7 years ago
• sethhirsh / BayesianSindy
  ☆13Updated 3 years ago
• PredictiveIntelligenceLab / BayesianDifferentiableProgramming
  ☆21Updated 4 years ago
• duqbo / optdmd
  A MATLAB package for computing the optimized dynamic mode decomposition (DMD)
  ☆18Updated 6 years ago
• pswpswpsw / SKDMD
  Sparsity-promoting Kernel Dynamic Mode Decomposition for Nonlinear Dynamical Systems
  ☆28Updated 2 years ago
• kpchamp / MultiscaleDiscovery
  ☆27Updated 6 years ago
• snagcliffs / parametric-discovery
  ☆24Updated 6 years ago
• PhIMaL / DeePyMoD_torch
  Pytorch implementation of the DeepMoD algorithm: [arXiv:1904.09406]
  ☆32Updated last year
• biomathlab / PDElearning
  Code repository for the paper "Learning partial differential equations for biological transport models from noisy spatiotemporal data"
  ☆10Updated 5 years ago
• niallmm / Hybrid-SINDy
  Sparse Identification of Nonlinear Dynamics for Hybrid Systems
  ☆23Updated 6 years ago
• maziarraissi / PDE_GP
  Machine learning of linear differential equations using Gaussian processes
  ☆24Updated 6 years ago
• kpchamp / SINDySR3
  ☆27Updated 4 years ago
• CarlosJose126 / NeuralODE-ROM
  This repository contains the files used in the paper " Reduced-order Model for Fluid Flows via Neural Ordinary Differential Equations"
  ☆16Updated last year
• CraigGin / PDEKoopman2
  Update PDEKoopman code to Tensorflow 2
  ☆23Updated 3 years ago
• cwrowley / dmdtools
  A library of tools for computing variants of Dynamic Mode Decomposition
  ☆46Updated 7 years ago
• Jianxun-Wang / Physics-constrained-Bayesian-deep-learning
  Physics-Constrained Bayesian Neural Network for Fluid Flow Reconstruction with Sparse and Noisy Data
  ☆47Updated 4 years ago
• arvindmohan / LSTM_ROM_Arxiv
  A Deep Learning based Approach to Reduced Order Modeling for Turbulent Flow Control using LSTM Neural Networks. arXiv:1804.09269
  ☆41Updated 6 years ago
• pierremtb / UQPINNs-TF2.0
  TensorFlow 2.0 implementation of Yibo Yang, Paris Perdikaris’s adversarial Uncertainty Quantification in Physics Informed Neural Networks…
  ☆19Updated last year
• stefaniafresca / DL-ROM
  Source code for deep learning-based reduced order models in cardiac electrophysiology. Available on doi.org/10.1371/journal.pone.0239416.
  ☆15Updated last year
• loiseaujc / SINDy
  ☆41Updated 7 years ago
• maziarraissi / NumericalGP
  Numerical Gaussian Processes for Time-dependent and Non-linear Partial Differential Equations
  ☆67Updated 4 years ago
• SchatzLabGT / SymbolicRegression
  ☆11Updated 3 years ago
• kfukami / CNN-SINDy-MLROM
  Sample codes of CNN-SINDy based reduced-order modeling for fluid flows by Fukami et al., JFM 2021.
  ☆24Updated 3 years ago
• FrancescoRegazzoni / model-learning
  ☆11Updated 2 years ago
• zhbai / cDMDc
  Compressive dynamic mode decomposition with control for compressive system identification
  ☆38Updated 7 years ago
• erichson / ShallowDecoder
  Shallow Learning for Flow Reconstruction with Limited Sensors and Limited Data
  ☆36Updated 6 years ago
• pygpc-polynomial-chaos / pygpc
  A Sensitivity and uncertainty analysis toolbox for Python based on the generalized polynomial chaos method
  ☆79Updated this week
• cselab / LED
  ☆19Updated 2 years ago
• zabaras / deep-turbulence
  Multi-fidelity Generative Deep Learning Turbulent Flows
  ☆37Updated 4 years ago