Google's Operations Research tools:
- combinatorial-optimization
- linear-programming
- operations-research
- optimization
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Google's Operations Research tools:
CUDA Templates and Python DSLs for High-Performance Linear Algebra
High performance, easy-to-use, and scalable machine learning (ML) package, including linear model (LR), factorization machines (FM), and field-aware factorization machines (FFM) for Python and CLI interface.
CasADi is a symbolic framework for numeric optimization implementing automatic differentiation in forward and reverse modes on sparse matrix-valued computational graphs. It supports self-contained C-code generation and interfaces state-of-the-art codes such as SUNDIALS, IPOPT etc. It can be used from C++, Python, Matlab/Octave, Julia or Javascript
Custom memory allocators in C++ to improve the performance of dynamic memory allocation
robot_localization is a package of nonlinear state estimation nodes. The package was developed by Charles River Analytics, Inc. Please ask questions on answers.ros.org.
DirectXMath is an all inline SIMD C++ linear algebra library for use in games and graphics apps
C++ library for solving large sparse linear systems with algebraic multigrid method
A header-only C++ library for large scale eigenvalue problems
Polygonal Surface Reconstruction from Point Clouds (C++ & Python)
Numerical linear algebra software package
Dense and sparse linear algebra library for Ruby via SciRuby
A framework for high-performance domain decomposition methods.
This is the Ruby interface to LIBLINEAR (much more efficient than LIBSVM for text classification and other large linear classifications)
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