Alternatives and similar repositories for SMCPy

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

• nasa / MLMCPy
  ☆71Updated 2 years ago
• florisvb / PyNumDiff
  Methods for numerical differentiation of noisy data in python
  ☆122Updated this week
• equadratures / equadratures
  ☆99Updated last year
• dynamicslab / pysensors
  PySensors is a Python package for sparse sensor placement
  ☆93Updated this week
• lanl / SEPIA
  Simulation-Enabled Prediction, Inference, and Analysis: physics-informed statistical learning.
  ☆35Updated last year
• pygpc-polynomial-chaos / pygpc
  A Sensitivity and uncertainty analysis toolbox for Python based on the generalized polynomial chaos method
  ☆81Updated last month
• stur86 / tvregdiff
  Python version of Rick Chartrand's algorithm for numerical differentiation of noisy data
  ☆73Updated 4 years ago
• luckystarufo / pySINDy
  SINDy (Sparse Identification of Nonlinear Dynamics) algorithms
  ☆79Updated 2 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
• hplgit / odespy
  Easy access in Python to a large collection of ODE solvers
  ☆123Updated 5 years ago
• simetenn / uncertainpy
  Uncertainpy: a Python toolbox for uncertainty quantification and sensitivity analysis, tailored towards computational neuroscience.
  ☆228Updated 2 years ago
• andreikitaitsev / SymINDy
  Symbolic Identification of Non-linear Dynamics. The method generalizes the SINDy algorithm by combining sparse and genetic-programming-ba…
  ☆76Updated 3 years ago
• leakec / tfc
  The Theory of Functional Connections: A functional interpolation method with applications in solving differential equations.
  ☆40Updated this week
• sandialabs / pyapprox
  Flexible and efficient tools for high-dimensional approximation, scientific machine learning and uncertainty quantification.
  ☆64Updated last week
• sigma-py / smoothfit
  Smooth data fitting in N dimensions.
  ☆56Updated 2 years ago
• numericalalgorithmsgroup / dfols
  Python-based Derivative-Free Optimizer for Least-Squares
  ☆42Updated 6 months ago
• scottshambaugh / monaco
  Quantify uncertainty and sensitivities in your computer models with an industry-grade Monte Carlo library.
  ☆119Updated 3 weeks ago
• andgoldschmidt / derivative
  Optimal numerical differentiation of noisy time series data in python.
  ☆64Updated last month
• IvanYashchuk / fenics-pymc3
  Differentiable interface to FEniCS for PyMC3
  ☆20Updated 2 years ago
• SURGroup / UQpy
  UQpy (Uncertainty Quantification with python) is a general purpose Python toolbox for modeling uncertainty in physical and mathematical s…
  ☆323Updated last month
• prmiles / pymcmcstat
  Python implementation of MATLAB toolbox "mcmcstat"
  ☆72Updated 3 years ago
• pymc-devs / sunode
  Solve ODEs fast, with support for PyMC
  ☆114Updated last year
• erichson / DMDpack
  Dynamic Mode Decomposition
  ☆60Updated 8 years ago
• sandialabs / UQTk
  Sandia Uncertainty Quantification Toolkit
  ☆82Updated 8 months ago
• numericalalgorithmsgroup / pybobyqa
  Python-based Derivative-Free Optimization with Bound Constraints
  ☆86Updated 11 months ago
• pdfo / pdfo
  Powell's Derivative-Free Optimization solvers.
  ☆103Updated 3 months ago
• nasa / UQPCE
  Uncertainty Quantification using Polynomial Chaos Expansion (UQPCE) is an open-source, python-based research code for use in parametric, …
  ☆49Updated 2 weeks ago
• rickchartrand / regularized_differentiation
  Numerical differentiation with regularization, allowing differentiation of noisy data without amplifying noise. Uses total variation and …
  ☆30Updated 6 years ago
• bluescarni / heyoka.py
  Python library for ODE integration via Taylor's method and LLVM
  ☆78Updated this week
• pints-team / pints
  Probabilistic Inference on Noisy Time Series
  ☆239Updated 6 months ago