OpenShot Video Editor is a non-linear video editor for Linux, built with Python, GTK, and the MLT Framework. Our goal is to create an easy-to-use, powerful, non-linear video editor, with a focus on "User Interface", "Work flow", and "Stability".
The Trilinos Project is an effort to develop algorithms and enabling technologies within an object-oriented software framework for the solution of large-scale, complex multi-physics engineering and scientific problems. A unique design feature of Trilinos is its focus on packages.
Trilinos
... [More] provides capabilities in meshing, load balancing, discretizations, mathematical optimization and uncertainty quantification, and transient, nonlinear, and linear solvers. Trilinos software is designed for scalability on the largest computer systems available and represents the state-of-the-art in scalable unstructured linear algebra, scalable unstructured preconditioning, block iterative methods, embedded optimization, stochastic methods, compatible discretizations and parallel partitioning algorithms. [Less]
RobOptim is a generic C++ nonlinear optimization library for robotics. The core level allows users to define optimization problems in a generic way in order to use different back-ends.
The minfx project is a Python package for numerical optimisation, being a large collection of standard minimisation algorithms. This includes the line search methods: steepest descent, back-and-forth coordinate descent, quasi-Newton BFGS, Newton, Newton-CG; the trust-region methods: Cauchy
... [More] point, dogleg, CG-Steihaug, exact trust region; the conjugate gradient methods: Fletcher-Reeves, Polak-Ribiere, Polak-Ribiere +, Hestenes-Stiefel; the miscellaneous methods: Grid search, Simplex, Levenberg-Marquardt; and the augmented function constraint algorithms: logarithmic barrier and method of multipliers (or augmented Lagrangian method). [Less]
Ceres Solver is a portable C++ library that allows for modeling and solving large complicated nonlinear least squares problems. Features include:
* A friendly API: build your objective function one term at a time.
* Automatic differentiation.
* Robust loss functions.
* Local
... [More] parameterizations.
* Threaded Jacobian evaluators and linear solvers.
* Levenberg-Marquardt and Dogleg (Powell & Subspace) solvers.
* Dense QR and Cholesky factorization (using Eigen) for small problems.
* Sparse Cholesky factorization (using SuiteSparse) for large sparse problems.
* Specialized solvers for bundle adjustment problems in computer vision.
* Iterative linear solvers for general sparse and bundle adjustment problems. [Less]
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