Alternatives and similar repositories for pde

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

• ngorbach / Variational_Gradient_Matching_for_Dynamical_Systems
  Sample code for the NIPS paper "Scalable Variational Inference for Dynamical Systems"
  ☆26Updated 6 years ago
• maziarraissi / ParametricGP
  Parametric Gaussian Process Regression for Big Data
  ☆45Updated 5 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
  ☆26Updated 3 years ago
• keisuke198619 / GraphDMD
  Dynamic mode decomposition with dependent structure among observables (Graph DMD)
  ☆13Updated 5 years ago
• maziarraissi / ParametricGP-in-Matlab
  Parametric Gaussian Process Regression for Big Data (Matlab Version)
  ☆24Updated 7 years ago
• amkatrutsa / DeepPDE
  Deep Learning application to the partial differential equations
  ☆30Updated 7 years ago
• AlexTMallen / koopman-forecasting
  Long-term probabilistic forecasting of quasiperiodic phenomena using Koopman theory
  ☆36Updated 3 years ago
• erichson / DMDpack
  Dynamic Mode Decomposition
  ☆59Updated 7 years ago
• ZichaoLong / aTEAM
  A pyTorch Extension for Applied Mathematics
  ☆39Updated 5 years ago
• snagcliffs / RKNN
  ☆20Updated 6 years ago
• maziarraissi / MultistepNNs
  Multistep Neural Networks for Data-driven Discovery of Nonlinear Dynamical Systems
  ☆63Updated 5 years ago
• duke-mlss / Duke-MLWS-2019
  Duke Machine Learning Winter School 2019
  ☆27Updated 6 years ago
• aaren / sparse_dmd
  sparse dynamic mode decomposition in python
  ☆37Updated 9 years ago
• kpchamp / MultiscaleDiscovery
  ☆28Updated 7 years ago
• Romit-Maulik / Practice
  Random snippets of code I've developed over the years (generally when bored)
  ☆12Updated 2 years ago
• maziarraissi / PDE_GP
  Machine learning of linear differential equations using Gaussian processes
  ☆24Updated 7 years ago
• PhIMaL / DeePyMoD_tensorflow
  This implementation of DeePyMoD is no longer maintained! We switched to a PyTorch based implementation: https://github.com/PhIMaL/DeePyM…
  ☆24Updated 5 years ago
• sayin / Data_Driven_Symbolic_Regression
  Interpretable machine learning (symbolic regression) using Genetic programming/Gene expression programming and Sparse regression used …
  ☆33Updated 4 years ago
• jbharley / WISP
  The WISP (Wave Integrated Signal Processing) repository for analyzing complex wave propogation in guided wave nondestructive testing and …
  ☆17Updated 10 years ago
• IPAIopen / NumDL-CourseNotes
  Course notes for graduate-level class on numerical methods for deep learning
  ☆51Updated 4 years ago
• jesserobertson / pydym
  Dynamic mode decomposition in Python
  ☆13Updated 10 years ago
• n-takeishi / bayesiandmd
  Bayesian Dynamic Mode Decomposition (Bayesian DMD)
  ☆18Updated 3 years ago
• briandesilva / discovery-of-physics-from-data
  Code to accompany the paper "Discovery of Physics from Data: Universal Laws and Discrepancies"
  ☆27Updated 5 years ago
• loiseaujc / SINDy
  ☆41Updated 7 years ago
• maziarraissi / NumericalGP
  Numerical Gaussian Processes for Time-dependent and Non-linear Partial Differential Equations
  ☆69Updated 5 years ago
• maziarraissi / TutorialGP
  Tutorial on Gaussian Processes
  ☆62Updated 5 years ago
• fernexda / cnm
  ☆18Updated 4 years ago
• kailaix / nnpde
  CS230 Project: Deep Learning for PDE
  ☆41Updated 7 years ago
• paraklas / GPTutorial
  A hands-on tutorial on supervised learning with Gaussian processes
  ☆37Updated 5 years ago
• Tom-Ryder / VIforSDEs
  A variational method for fast, approximate inference for stochastic differential equations.
  ☆44Updated 7 years ago