numerical-methods

High-performance TensorFlow library for quantitative finance.

The Go kernel for Jupyter notebooks and nteract.

Parallel Computing and Scientific Machine Learning (SciML): Methods and Applications (MIT 18.337J/6.338J)

A PyTorch library entirely dedicated to neural differential equations, implicit models and related numerical methods

Kratos Multiphysics (A.K.A Kratos) is a framework for building parallel multi-disciplinary simulation software. Modularity, extensibility and HPC are the main objectives. Kratos has BSD license and is written in C++ with extensive Python interface.

Fortran Standard Library

Python library for arbitrary-precision floating-point arithmetic

Optimize floating-point expressions for accuracy

Grid-based approximation of partial differential equations in Julia

A C++ header-only library of statistical distribution functions.

Quantitative Interview Preparation Guide, updated version here ==>

Numerical Analysis Implementations in Various Languages

Probabilistic Numerics in Python.

Python package for numerical derivatives and partial differential equations in any number of dimensions.

Materials for book: "Markov Chains for programmers"

PDE-Net: Learning PDEs from Data

PyDEns is a framework for solving Ordinary and Partial Differential Equations (ODEs & PDEs) using neural networks

The official implementation for Pseudo Numerical Methods for Diffusion Models on Manifolds (PNDM, PLMS | ICLR2022)

An interactive book about the Riemann problem for hyperbolic PDEs, using Jupyter notebooks.

compilable markdown for linear algebra