#Numerical-methods
Showing 24 of 24 repositories tagged #numerical-methods, ranked by stars
High-performance TensorFlow library for quantitative finance.
The Go kernel for Jupyter notebooks and nteract.
A PyTorch library entirely dedicated to neural differential equations, implicit models and related numerical methods
Python library for arbitrary-precision floating-point arithmetic
Quantitative Interview Preparation Guide, updated version here ==>
Optimize floating-point expressions for accuracy
Directory of Fortran codes on GitHub, arranged by topic
PyTorch for Quantitative Finance : Refine Derivatives Hedging and Pricing with Architecture Alightment in Operators
Data science and Big Data with Python
Generative Pre-Trained Physics-Informed Neural Networks Implementation
Python library for simulating heat transfer processes
This repository contains code released by DiffEqML Research
Python-based Derivative-Free Optimization with Bound Constraints
Generalized (hyper-) dual numbers in rust
Code for "'Hey, that's not an ODE:' Faster ODE Adjoints via Seminorms" (ICML 2021)
RustyNum: A NumPy Alternative powered by Rust’s Portable SIMD
High level linear algebra library for Dlang
A LAPACK implementation for Go [DEPRECATED]
Examples and demos showing how to call functions from the nAG Library for Python
Numerical Methods Lecture: This repository contains the material created during the lecture Numerical Methods for Mathematical Finance.
Notes and examples on how to solve partial differential equations with numerical methods, using Python.
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A bioinformatics-focused library for numerical modeling, optimisation, and simulation written in Rust
Low-latency options pricing engine in Rust. BSM, Black-76, Heston, Bates (stochastic vol + jumps), Local Vol (Dupire). Analytic Greeks, fast IV solver (Halley), monotone cubic spline surfaces. Parallel batch pricing via Rayon.