Alternatives and similar repositories for PDElearning:

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

• PhIMaL / DeePyMoD_torch
  Pytorch implementation of the DeepMoD algorithm: [arXiv:1904.09406]
  ☆32Updated 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
• snagcliffs / parametric-discovery
  ☆24Updated 6 years ago
• Zhengyu-Huang / Operator-Learning
  ☆40Updated 2 years ago
• fernexda / cnm
  ☆18Updated 4 years ago
• PredictiveIntelligenceLab / TRIPODS_Winter_School_2022
  Practicum on Supervised Learning in Function Spaces
  ☆32Updated 3 years ago
• RizaXudayi / VarNet
  Variational Neural Networks for the Solution of Partial Differential Equations
  ☆8Updated 5 years ago
• pswpswpsw / paper-nif
  ☆35Updated last year
• sethhirsh / BayesianSindy
  ☆14Updated 3 years ago
• AmeyaJagtap / Locally-Adaptive-Activation-Functions-Neural-Networks-
  Python codes for Locally Adaptive Activation Function (LAAF) used in deep neural networks. Please cite this work as "A D Jagtap, K Kawa…
  ☆39Updated 2 years ago
• cselab / LED
  ☆19Updated 2 years ago
• Jianxun-Wang / Physics-constrained-Bayesian-deep-learning
  Physics-Constrained Bayesian Neural Network for Fluid Flow Reconstruction with Sparse and Noisy Data
  ☆48Updated 4 years ago
• panchgonzalez / nmor
  Deep learning framework for model reduction of dynamical systems
  ☆21Updated 4 years ago
• maziarraissi / MultistepNNs
  Multistep Neural Networks for Data-driven Discovery of Nonlinear Dynamical Systems
  ☆63Updated 5 years ago
• CognitiveModeling / finn
  The public repository about our joint FINN research project
  ☆36Updated 2 years ago
• peterparity / PDE-VAE-pytorch
  PDE-VAE: Variational Autoencoder for Extracting Interpretable Physical Parameters from Spatiotemporal Systems using Unsupervised Learning
  ☆35Updated 3 years ago
• maziarraissi / NumericalGP
  Numerical Gaussian Processes for Time-dependent and Non-linear Partial Differential Equations
  ☆67Updated 4 years ago
• CraigGin / PDEKoopman2
  Update PDEKoopman code to Tensorflow 2
  ☆23Updated 3 years ago
• katiana22 / GDM-PCE
  Source code of: "Manifold learning-based polynomial chaos expansions for high-dimensional surrogate models".
  ☆37Updated 2 years ago
• jcallaham / robust-flow-reconstruction
  Code for "Robust flow field reconstruction from limited measurements vis sparse representation" (J. Callaham, K. Maeda, and S. Brunton 20…
  ☆14Updated 6 years ago
• dynamicslab / langevin-regression
  Code for "Nonlinear stochastic modeling with Langevin regression" J. L. Callaham, J.-C. Loiseau, G. Rigas, and S. L. Brunton
  ☆25Updated 3 years ago
• pswpswpsw / SKDMD
  Sparsity-promoting Kernel Dynamic Mode Decomposition for Nonlinear Dynamical Systems
  ☆28Updated 2 years ago
• pehersto / mfmc
  Multi Fidelity Monte Carlo
  ☆25Updated 5 years ago
• peterparity / symder
  SymDer: Symbolic Derivative Approach to Discovering Sparse Interpretable Dynamics from Partial Observations
  ☆20Updated 2 years ago
• fsahli / EikonalNet
  ☆19Updated 4 years ago
• dynamicslab / dominant-balance
  Methods and code for J. L. Callaham, J. N. Kutz, B. W. Brunton, and S. L. Brunton (2020)
  ☆56Updated 4 years ago
• elizqian / operator-inference
  ☆10Updated last year
• dbgannon / NNets-and-Diffeqns
  jupyter notebooks for the neural nets and differential equation paper
  ☆28Updated 3 years ago
• maziarraissi / PDE_GP
  Machine learning of linear differential equations using Gaussian processes
  ☆24Updated 6 years ago
• jayroxis / qres
  Learning with Higher Expressive Power than Neural Networks (On Learning PDEs)
  ☆15Updated 4 years ago