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
• sethhirsh / BayesianSindy
  ☆14Updated 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.
  ☆26Updated 4 years ago
• dynamicslab / dominant-balance
  Methods and code for J. L. Callaham, J. N. Kutz, B. W. Brunton, and S. L. Brunton (2020)
  ☆59Updated 4 years ago
• Jianxun-Wang / Physics-constrained-Bayesian-deep-learning
  Physics-Constrained Bayesian Neural Network for Fluid Flow Reconstruction with Sparse and Noisy Data
  ☆49Updated 5 years ago
• loiseaujc / SINDy
  ☆41Updated 7 years ago
• pswpswpsw / SKDMD
  Sparsity-promoting Kernel Dynamic Mode Decomposition for Nonlinear Dynamical Systems
  ☆30Updated 3 years ago
• snagcliffs / parametric-discovery
  ☆26Updated 7 years ago
• isds-neu / PiSL
  A python implementation of Physics-informed Spline Learning for nonlinear dynamics discovery.
  ☆27Updated 4 years ago
• cselab / LED
  ☆21Updated 2 years ago
• PredictiveIntelligenceLab / UQPINNs
  ☆63Updated 6 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"
  ☆19Updated 2 years ago
• PredictiveIntelligenceLab / BayesianDifferentiableProgramming
  ☆21Updated 5 years ago
• ashesh6810 / RCESN_spatio_temporal
  Spatio-temporal forecasting of Lorenz96 with RC-ESN, RNN-LSTM and ANN
  ☆44Updated 5 years ago
• LivingMatterLab / xPINNs
  when using, please cite "Bayesian Physics-Informed Neural Networks for real-world nonlinear dynamical systems", CMAME, https://doi.org/1…
  ☆78Updated 3 years ago
• dynamicslab / pysensors
  PySensors is a Python package for sparse sensor placement
  ☆106Updated 3 weeks 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
• ehsankharazmi / PINN-COVID
  PINN-COVID analyzes a plurality of epidemiological models through the lens of physics-informed neural networks (PINNs).
  ☆22Updated 4 years ago
• SchatzLabGT / SymbolicRegression
  ☆11Updated 4 years ago
• sisl / deep_flow_control
  Source code for "Deep Dynamical Modeling and Control of Unsteady Fluid Flows" from NeurIPS 2018
  ☆49Updated 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…
  ☆21Updated 2 years ago
• cwrowley / dmdtools
  A library of tools for computing variants of Dynamic Mode Decomposition
  ☆49Updated 8 years ago
• luckystarufo / pySINDy
  SINDy (Sparse Identification of Nonlinear Dynamics) algorithms
  ☆79Updated 2 years ago
• pehersto / mfmc
  Multi Fidelity Monte Carlo
  ☆24Updated 5 years ago
• cics-nd / cnn-surrogate
  Bayesian deep convolutional encoder-decoder networks for surrogate modeling and uncertainty quantification
  ☆107Updated 5 years ago
• remcovandermeer / Optimally-Weighted-PINNs
  ☆42Updated 5 years ago
• PhIMaL / DeePyMoD_torch
  Pytorch implementation of the DeepMoD algorithm: [arXiv:1904.09406]
  ☆33Updated 2 years ago
• PhIMaL / DeePyMoD
  ☆49Updated 2 years ago
• fernexda / cnm
  ☆19Updated 5 years ago
• CraigGin / PDEKoopman2
  Update PDEKoopman code to Tensorflow 2
  ☆23Updated 4 years ago