Results for dual_num

Fully-featured Dual Number implementation with features for automatic differentiation of multivariate vectorial functions into gradients

Generalized (hyper) dual numbers for the calculation of exact (partial) derivatives

This package implements general one-dimensional root-finding algorithms built on the shoulders of the num_dual crate

A high-performance automatic differentiation library for Rust

A memory-safe interior point optimizer in Rust

Python bindings for num-dual: Generalized (hyper) dual numbers for the calculation of exact (partial) derivatives

Blackbox NLP solver using IPOPT and automatic differentiation

odesign is an optimal design of experiments library written in pure rust.

odesign is an optimal design of experiments library written in pure rust.

FeOs-AD - Implicit automatic differentiation of equations of state and phase equilibria.

Forward auto-differentiation, allowing its user to manage memory location and minimize copying.

Pure-Rust AV1 codec — orphan-rebuild scaffold pending clean-room re-implementation.