numerical-methods

The Go kernel for Jupyter notebooks and nteract.

High-performance TensorFlow library for quantitative finance.

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

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

The official implementation for Pseudo Numerical Methods for Diffusion Models on Manifolds (ICLR 2022) and a generic framework for DDIM-like models

Topological Data Analysis in Python