mattja / sdeintLinks
Numerical integration of Ito or Stratonovich SDEs
☆167Updated 2 years ago
Alternatives and similar repositories for sdeint
Users that are interested in sdeint are comparing it to the libraries listed below
Sorting:
- kramersmoyal: Kramers-Moyal coefficients for stochastic data of any dimension, to any desired order☆74Updated 8 months ago
- Quasi-Monte Carlo point generators, automatic transformations, and adaptive stopping criteria☆76Updated this week
- Probabilistic Inference on Noisy Time Series☆239Updated 6 months ago
- Manifold Markov chain Monte Carlo methods in Python☆232Updated 3 weeks ago
- Probabilistic Numerics in Python.☆455Updated 2 months ago
- Methods for numerical differentiation of noisy data in python☆122Updated this week
- python version of the No-U-Turn Sampler (NUTS) from Hoffman & Gelman, 2011☆132Updated 4 years ago
- Deep GPs built on top of TensorFlow/Keras and GPflow☆127Updated 10 months ago
- A LinearOperator implementation to wrap the numerical nuts and bolts of GPyTorch☆112Updated 5 months ago
- Python-based Derivative-Free Optimization with Bound Constraints☆87Updated 11 months ago
- A Python implementation of Chebfun☆142Updated this week
- Solve ODEs fast, with support for PyMC☆114Updated last year
- Python version of Rick Chartrand's algorithm for numerical differentiation of noisy data☆73Updated 4 years ago
- Solving stochastic differential equations and Kolmogorov equations by means of deep learning and Multilevel Monte Carlo simulation☆12Updated 4 years ago
- Differentiable interface to FEniCS/Firedrake for JAX using dolfin-adjoint/pyadjoint☆99Updated last year
- Simplicial Homology Global Optimization☆53Updated 5 months ago
- Gaussian process modelling in Python☆222Updated 8 months ago
- Solve automatic numerical differentiation problems in one or more variables.☆268Updated 2 years ago
- A JAX-based research framework for writing differentiable numerical simulators with arbitrary discretizations☆130Updated 11 months ago
- Turning SymPy expressions into PyTorch modules.