8 dépôts
Mathematical libraries for solving least-squares and nonlinear optimization problems.
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SciPy is a scientific computing library for Python that provides a comprehensive collection of mathematical algorithms and numerical tools for research and engineering. It functions as a high-performance numerical analysis framework, bridging high-level Python code with compiled C and Fortran routines to execute complex computations at hardware speeds. The library is built upon array-based data structures that utilize strided memory layouts to enable efficient data manipulation and slicing. By employing vectorized operation dispatch and linking to optimized hardware-specific linear algebra li
Python-based optimization functions for least-squares problems.
dlib is a C++ machine learning toolkit and data analysis framework. It provides a collection of algorithms and utilities for building predictive modeling applications and performing statistical analysis on large datasets within native C++ environments. The project functions as a binding library that wraps low-level C++ machine learning algorithms into high-level Python scripting interfaces. This allows for the integration of high-performance native implementations with Python for machine learning development. The framework covers the implementation of predictive models, the execution of mach
Toolkit providing functions for solving least-squares problems.
Ceres Solver est une bibliothèque C++ pour l'optimisation numérique, spécialisée dans les problèmes de moindres carrés non linéaires et d'optimisation sans contrainte. Elle sert de framework pour la différenciation automatique et l'ajustement de courbe robuste, fournissant des outils pour résoudre des modèles mathématiques à grande échelle. La bibliothèque se distingue par ses capacités d'ajustement de faisceau (bundle adjustment), qui exploitent des structures de matrices creuses pour affiner les points de scène 3D et les paramètres de caméra. Elle utilise la différenciation automatique par nombres duaux pour calculer les dérivées des fonctions de coût, supprimant le besoin de dérivation manuelle du Jacobien. Le projet couvre un large éventail de capacités d'optimisation, y compris les contraintes de variété pour les espaces non euclidiens, les fonctions de perte robustes pour atténuer les valeurs aberrantes, et la résolution de systèmes linéaires denses et creux. Elle fournit également des utilitaires pour la conversion de représentation de rotation, l'interpolation de données tabulées et l'estimation de covariance de paramètres. Des configurations de build sont disponibles pour les cibles Android et iOS afin de prendre en charge l'optimisation du matériel mobile.
C++ library for large-scale nonlinear optimization problems.
Drake is a robotics simulation framework and control system modeling tool used for designing, simulating, and verifying the dynamics of complex robotic systems. It functions as a multibody dynamics simulator and a mathematical optimization library, providing a suite of algorithms for trajectory optimization and the simulation of articulated robots. The framework is distinguished by its block-diagram system for composing dynamical subsystems and its ability to formulate and solve diverse mathematical programs, including linear, quadratic, and nonconvex nonlinear problems. It supports specializ
Offers a toolkit for formulating and solving linear, quadratic, and nonlinear optimization problems for trajectory planning.
GTSAM is a library of C++ classes that implement smoothing and mapping (SAM) in robotics and vision, using factor graphs and Bayes networks as the underlying computing paradigm rather than sparse matrices.
Library for factor graphs and optimization in robotics and vision.
g2o: A General Framework for Graph Optimization
Framework for optimizing graph-based nonlinear error functions.
Symbolic computation and nonlinear optimization for robotics.
LMfit-py
Python package extending optimization methods for least-squares.