Numerical Optimization
Showing 9 of 9 projects
A high-performance TensorFlow library for quantitative finance, providing mathematical methods, pricing models, and calibration tools.
A comprehensive Python library for solving optimal transport problems with solvers for linear, entropic, Gromov-Wasserstein, and unbalanced OT, plus machine learning applications.
A minimal, well-tested library for training and using feedforward artificial neural networks in ANSI C.
A pure Rust numerical optimization library offering a wide range of algorithms with a consistent, type-agnostic interface.
A JAX-powered library for solving large-scale optimal transport problems, including matching, barycenters, and neural approximations.
A Python toolbox for solving optimal transport problems with JAX-powered computational efficiency.
A collection of optimization algorithms and logging utilities for Torch machine learning models.
A lightweight Bayesian optimization library built on JAX for efficient optimization of expensive-to-evaluate functions.
A Common Lisp library implementing evolutionary algorithms including Genetic Programming and Differential Evolution for optimization tasks.
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