Alternatives and similar repositories for sdeint:

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

• LRydin / KramersMoyal
  kramersmoyal: Kramers-Moyal coefficients for stochastic data of any dimension, to any desired order
  ☆72Updated 3 months ago
• matt-graham / mici
  Manifold Markov chain Monte Carlo methods in Python
  ☆228Updated 2 months ago
• xwinxu / bayeSDE
  Code for "Infinitely Deep Bayesian Neural Networks with Stochastic Differential Equations"
  ☆169Updated 3 years ago
• mattja / nsim
  Large scale simulation of ODEs or SDEs, analyze time series.
  ☆25Updated 5 years ago
• secondmind-labs / GPflux
  Deep GPs built on top of TensorFlow/Keras and GPflow
  ☆124Updated 5 months ago
• alu042 / SDE-higham
  Some basic algorithms for stochastic differential equations in Python/NumPy
  ☆28Updated 11 years ago
• neurophysik / jitcode
  Just-in-Time Compilation for Ordinary Differential Equations
  ☆63Updated last month
• stur86 / tvregdiff
  Python version of Rick Chartrand's algorithm for numerical differentiation of noisy data
  ☆70Updated 4 years ago
• pymc-devs / sunode
  Solve ODEs fast, with support for PyMC
  ☆112Updated 10 months ago
• QMCSoftware / QMCSoftware
  ☆66Updated this week
• numericalalgorithmsgroup / pybobyqa
  Python-based Derivative-Free Optimization with Bound Constraints
  ☆78Updated 6 months ago
• chebpy / chebpy
  A Python implementation of Chebfun
  ☆136Updated last year
• florisvb / PyNumDiff
  Methods for numerical differentiation of noisy data in python
  ☆116Updated 3 weeks ago
• IvanYashchuk / jax-fenics-adjoint
  Differentiable interface to FEniCS/Firedrake for JAX using dolfin-adjoint/pyadjoint
  ☆93Updated last year
• tonyshardlow / PICSPDE
  Python codes for Introduction to Computational Stochastic PDE
  ☆41Updated last month
• pints-team / pints
  Probabilistic Inference on Noisy Time Series
  ☆234Updated last month
• jeremiecoullon / SGMCMCJax
  Lightweight library of stochastic gradient MCMC algorithms written in JAX.
  ☆102Updated last year
• juliusberner / Deep-Multilevel-Kolmogorov-PDE-Solver
  Solving stochastic differential equations and Kolmogorov equations by means of deep learning and Multilevel Monte Carlo simulation
  ☆12Updated 3 years ago
• cornellius-gp / linear_operator
  A LinearOperator implementation to wrap the numerical nuts and bolts of GPyTorch
  ☆107Updated 3 weeks ago
• j-wilson / GPflowSampling
  Code for efficiently sampling functions from GP(flow) posteriors
  ☆72Updated 4 years ago
• Ambrosys / glyph
  a python 3 library based on deap providing abstraction layers for symbolic regression problems.
  ☆93Updated 3 years ago
• gpapamak / snl
  Sequential Neural Likelihood
  ☆39Updated 5 years ago
• jacobjinkelly / easy-neural-ode
  Code for the paper "Learning Differential Equations that are Easy to Solve"
  ☆278Updated 3 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
• horchler / SDETools
  Matlab Toolbox for the Numerical Solution of Stochastic Differential Equations
  ☆101Updated 4 years ago
• ColCarroll / minimc
  Just a little MCMC
  ☆223Updated 9 months ago
• minaskar / zeus
  ⚡️ zeus: Lightning Fast MCMC ⚡️
  ☆233Updated last year
• ucl-bug / jaxdf
  A JAX-based research framework for writing differentiable numerical simulators with arbitrary discretizations
  ☆123Updated 6 months ago
• kazewong / flowMC
  Normalizing-flow enhanced sampling package for probabilistic inference in Jax
  ☆228Updated last week
• esa / torchquad
  Numerical integration in arbitrary dimensions on the GPU using PyTorch / TF / JAX
  ☆201Updated 4 months ago