Collection of notebooks about quantitative finance, with interactive python code.

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.

NMA Computational Neuroscience course

Gaussian processes in TensorFlow

Differentiable SDE solvers with GPU support and efficient sensitivity analysis.

Generate realizations of stochastic processes in python.

Python framework for short-term ensemble prediction systems.

Rust library for quantitative finance.

Solvers for stochastic differential equations which connect with the scientific machine learning (SciML) ecosystem

Code for the Neural Processes website and replication of 4 papers on NPs. Pytorch implementation.

Language modeling via stochastic processes. Oral @ ICLR 2022.

Multifractal Detrended Fluctuation Analysis in Python

R package for statistical inference using partially observed Markov processes

Economic scenario generator for python: simulate stocks, interest rates, and other stochastic processes.

Matlab Toolbox for the Numerical Solution of Stochastic Differential Equations

A library of noise processes for stochastic systems like stochastic differential equations (SDEs) and other systems that are present in scientific machine learning (SciML)

Implement pricing analytics and Monte Carlo simulations for stochastic volatility models including log-normal SV model, Heston

Tools to generate and study moment equations for any chemical reaction network using various moment closure approximations

📦 Python library for Stochastic Processes Simulation and Visualisation

By means of stochastic volatility models