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 last month
• tonyshardlow / PICSPDE
  Python codes for Introduction to Computational Stochastic PDE
  ☆40Updated this week
• johnaparker / fplanck
  Numerically solve the Fokker-Planck equation in N dimensions
  ☆88Updated last year
• xwinxu / bayeSDE
  Code for "Infinitely Deep Bayesian Neural Networks with Stochastic Differential Equations"
  ☆169Updated 3 years ago
• QMCSoftware / QMCSoftware
  ☆64Updated this week
• alu042 / SDE-higham
  Some basic algorithms for stochastic differential equations in Python/NumPy
  ☆28Updated 11 years ago
• matt-graham / mici
  Manifold Markov chain Monte Carlo methods in Python
  ☆226Updated 3 weeks ago
• mattja / nsim
  Large scale simulation of ODEs or SDEs, analyze time series.
  ☆25Updated 5 years ago
• ucl-bug / jaxdf
  A JAX-based research framework for writing differentiable numerical simulators with arbitrary discretizations
  ☆123Updated 4 months 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 2 years ago
• florisvb / PyNumDiff
  Methods for numerical differentiation of noisy data in python
  ☆114Updated this week
• 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
• numericalalgorithmsgroup / pybobyqa
  Python-based Derivative-Free Optimization with Bound Constraints
  ☆79Updated 5 months ago
• jeremiecoullon / SGMCMCJax
  Lightweight library of stochastic gradient MCMC algorithms written in JAX.
  ☆100Updated last year
• IvanYashchuk / jax-fenics-adjoint
  Differentiable interface to FEniCS/Firedrake for JAX using dolfin-adjoint/pyadjoint
  ☆93Updated last year
• luckystarufo / pySINDy
  SINDy (Sparse Identification of Nonlinear Dynamics) algorithms
  ☆72Updated 2 years ago
• probabilistic-numerics / probnum
  Probabilistic Numerics in Python.
  ☆448Updated 9 months ago
• maziarraissi / FBSNNs
  Forward-Backward Stochastic Neural Networks: Deep Learning of High-dimensional Partial Differential Equations
  ☆150Updated 4 years ago
• pints-team / pints
  Probabilistic Inference on Noisy Time Series
  ☆231Updated this week
• RMT-TheoryAndPractice / RMT
  ☆111Updated 7 years ago
• cornellius-gp / linear_operator
  A LinearOperator implementation to wrap the numerical nuts and bolts of GPyTorch
  ☆104Updated 2 weeks ago
• Ambrosys / glyph
  a python 3 library based on deap providing abstraction layers for symbolic regression problems.
  ☆94Updated 3 years ago
• pymc-devs / sunode
  Solve ODEs fast, with support for PyMC
  ☆112Updated 9 months ago
• chi-feng / gp-demo
  Gaussian Process Regression Interactive Javascript Demo
  ☆54Updated 6 years ago
• pbrod / numdifftools
  Solve automatic numerical differentiation problems in one or more variables.
  ☆262Updated last year
• esa / torchquad
  Numerical integration in arbitrary dimensions on the GPU using PyTorch / TF / JAX
  ☆198Updated 2 months ago
• neurophysik / jitcode
  Just-in-Time Compilation for Ordinary Differential Equations
  ☆63Updated this week
• Tom-Ryder / VIforSDEs
  A variational method for fast, approximate inference for stochastic differential equations.
  ☆44Updated 6 years ago
• jacobjinkelly / easy-neural-ode
  Code for the paper "Learning Differential Equations that are Easy to Solve"
  ☆274Updated 3 years ago
• chebpy / chebpy
  A Python implementation of Chebfun
  ☆135Updated last year