Alternatives and similar repositories for langevin-regression

Users that are interested in langevin-regression are comparing it to the libraries listed below

• pswpswpsw / SKDMD
  Sparsity-promoting Kernel Dynamic Mode Decomposition for Nonlinear Dynamical Systems
  ☆30Updated 3 years ago
• maziarraissi / NumericalGP
  Numerical Gaussian Processes for Time-dependent and Non-linear Partial Differential Equations
  ☆69Updated 5 years ago
• dynamicslab / modified-SINDy
  Example code for paper: Automatic Differentiation to Simultaneously Identify Nonlinear Dynamics and Extract Noise Probability Distributio…
  ☆59Updated 3 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
• 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
• mathLab / ATHENA
  ATHENA: Advanced Techniques for High dimensional parameter spaces to Enhance Numerical Analysis
  ☆55Updated 2 years ago
• fernexda / cnm
  ☆19Updated 5 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
• elizqian / operator-inference
  ☆10Updated 2 years ago
• remcovandermeer / Optimally-Weighted-PINNs
  ☆42Updated 5 years ago
• maziarraissi / MultistepNNs
  Multistep Neural Networks for Data-driven Discovery of Nonlinear Dynamical Systems
  ☆63Updated 5 years ago
• loiseaujc / SINDy
  ☆41Updated 7 years ago
• luckystarufo / multiscale_HiTS
  ☆73Updated 5 years ago
• LRydin / KramersMoyal
  kramersmoyal: Kramers-Moyal coefficients for stochastic data of any dimension, to any desired order
  ☆75Updated 10 months ago
• MagriLab / KolSol
  Pseudospectral Kolmogorov Flow Solver
  ☆41Updated 2 years ago
• NBoulle / greenlearning
  Learning Green's functions of partial differential equations with deep learning.
  ☆72Updated last year
• kpchamp / MultiscaleDiscovery
  ☆30Updated 7 years ago
• Willcox-Research-Group / rom-operator-inference-Python3
  Operator Inference for data-driven, non-intrusive model reduction of dynamical systems.
  ☆75Updated last week
• erichson / DMDpack
  Dynamic Mode Decomposition
  ☆60Updated 8 years ago
• LLNL / LaSDI
  ☆54Updated 2 years ago
• atzberg / gmls-nets
  PyTorch implementation of GMLS-Nets. Machine learning methods for scattered unstructured data sets. Methods for learning differential op…
  ☆27Updated last month
• PredictiveIntelligenceLab / BayesianDifferentiableProgramming
  ☆21Updated 5 years ago
• pooyasf / DGM
  Solving High Dimensional Partial Differential Equations with Deep Neural Networks
  ☆34Updated 3 years ago
• juliusberner / Deep-Multilevel-Kolmogorov-PDE-Solver
  Solving stochastic differential equations and Kolmogorov equations by means of deep learning and Multilevel Monte Carlo simulation
  ☆12Updated 4 years ago
• IvanYashchuk / jax-fenics
  Differentiable interface to FEniCS for JAX
  ☆58Updated 4 years ago
• cselab / LED
  ☆21Updated 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
• DENG-MIT / StiffNeuralODE
  Stiff Neural Ordinary Differential Equations
  ☆35Updated 2 years ago
• dynamicslab / deep-learning-fluids
  A collection of codes and references for deep learning in fluid dynamics
  ☆19Updated 4 years ago