stochastic-differential-equations
There are 29 repositories under stochastic-differential-equations topic.
cantaro86 / Financial-Models-Numerical-Methods
Collection of notebooks about quantitative finance, with interactive python code.
quantitative-financejupyter-notebookskalman-filteroption-pricingfinancial-engineeringfinancial-mathematicspartial-differential-equationsfourier-inversionstochastic-processesstochastic-differential-equationslevy-processesheston-modelbrownian-motionamerican-optionsmonte-carlo-methodspythonlinear-regressionlinear-systems-equationsjump-diffusion-mertons-modeleconometricsLanguage:Jupyter Notebook 6482SciML / DifferentialEquations.jl
Multi-language suite for high-performance solvers of differential equations and scientific machine learning (SciML) components. Ordinary differential equations (ODEs), stochastic differential equations (SDEs), delay differential equations (DDEs), differential-algebraic equations (DAEs), and more in Julia.
Language:Julia 2999yang-song / score_sde_pytorch
PyTorch implementation for Score-Based Generative Modeling through Stochastic Differential Equations (ICLR 2021, Oral)
Language:Jupyter Notebook 2000Official code for Score-Based Generative Modeling through Stochastic Differential Equations (ICLR 2021, Oral)
Language:Jupyter Notebook 1726google-research / torchsde
Differentiable SDE solvers with GPU support and efficient sensitivity analysis.
Language:Python 1671An acausal modeling framework for automatically parallelized scientific machine learning (SciML) in Julia. A computer algebra system for integrated symbolics for physics-informed machine learning and automated transformations of differential equations
Language:Julia 1551Pre-built implicit layer architectures with O(1) backprop, GPUs, and stiff+non-stiff DE solvers, demonstrating scientific machine learning (SciML) and physics-informed machine learning methods
neural-odeneural-sdeneural-pdeneural-ddeneural-differential-equationsstiff-odeordinary-differential-equationsstochastic-differential-equationsdelay-differential-equationspartial-differential-equationsneural-networksdifferentialequationsdifferential-equationsscientific-mlscientific-aineural-jump-diffusionsneural-sdesscientific-machine-learningpinnphysics-informed-learningLanguage:Julia 894Tutorials for doing scientific machine learning (SciML) and high-performance differential equation solving with open source software.
Language:CSS 734Algolzw / image-restoration-sde
Image Restoration with Mean-Reverting Stochastic Differential Equations, ICML 2023. Winning solution of the NTIRE 2023 Image Shadow Removal Challenge.
Language:Python 677Solving differential equations in Python using DifferentialEquations.jl and the SciML Scientific Machine Learning organization
Language:Python 577crflynn / stochastic
Generate realizations of stochastic processes in python.
Language:Python 485LituRout / RF-Inversion
Rectified Flow Inversion (RF-Inversion) - ICLR 2025
Language:Python 456The lightweight Base library for shared types and functionality for defining differential equation and scientific machine learning (SciML) problems
Language:Julia 343quantgirluk / aleatory
📦 Python library for Stochastic Processes Simulation and Visualisation
Language:Python 338Solvers for stochastic differential equations which connect with the scientific machine learning (SciML) ecosystem
Language:Julia 302Linear operators for discretizations of differential equations and scientific machine learning (SciML)
Language:Julia 283- SDELanguage:MATLAB 197
harryjo97 / GDSS
Official Code Repository for the paper "Score-based Generative Modeling of Graphs via the System of Stochastic Differential Equations" (ICML 2022)
Language:Python 173xwinxu / bayeSDE
Code for "Infinitely Deep Bayesian Neural Networks with Stochastic Differential Equations"
Language:Python 171Solving differential equations in R using DifferentialEquations.jl and the SciML Scientific Machine Learning ecosystem
Language:R 145Extension functionality which uses Stan.jl, DynamicHMC.jl, and Turing.jl to estimate the parameters to differential equations and perform Bayesian probabilistic scientific machine learning
Language:Julia 125mschauer / Bridge.jl
A statistical toolbox for diffusion processes and stochastic differential equations. Named after the Brownian Bridge.
Language:Jupyter Notebook 112- Language:MATLAB 102
c-planelles / numerical-methods-fortran
Solving linear, nonlinear equations, ordinary differential equations, ... using numerical methods in fortran
Language:Fortran 101- Language:Python 97
A library of premade problems for examples and testing differential equation solvers and other SciML scientific machine learning tools
Language:Julia 80LRydin / KramersMoyal
kramersmoyal: Kramers-Moyal coefficients for stochastic data of any dimension, to any desired order
Language:Python 74juliusberner / sde_sampler
Improved sampling via learned diffusions (ICLR2024) and an optimal control perspective on diffusion-based generative modeling (TMLR2024)
Language:Python 66Easy scientific machine learning (SciML) parameter estimation with pre-built loss functions
Language:Julia 60jkirkby3 / pymle
Maximum Likelihood estimation and Simulation for Stochastic Differential Equations (Diffusions)
Language:Python 54JuliaGNI / GeometricIntegrators.jl
Geometric Numerical Integration in Julia
Language:Julia 50Tom-Ryder / VIforSDEs
A variational method for fast, approximate inference for stochastic differential equations.
Language:Python 44- Language:Python 43
cdriveraus / ctsem
Hierarchical continuous time state space modelling
Language:R 42bottama / stochastic-asset-pricing-in-continuous-time
Predicting stock prices using Geometric Brownian Motion and the Monte Carlo method
Language:Python 40LemurPwned / cmtj
Simulate multilayer magnetic structures in Python and C++
Language:Python 40
