Search Results for "decomposition"
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Showing 21 open source projects for "decomposition"
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AIMET
AIMET is a library that provides advanced quantization and compression
Qualcomm Innovation Center (QuIC) is at the forefront of enabling low-power inference at the edge through its pioneering model-efficiency research. QuIC has a mission to help migrate the ecosystem toward fixed-point inference. With this goal, QuIC presents the AI Model Efficiency Toolkit (AIMET) - a library that provides advanced quantization and compression techniques for trained neural network models. AIMET enables neural networks to run more efficiently on fixed-point AI hardware... -
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Armadillo
fast C++ library for linear algebra & scientific computing
* Fast C++ library for linear algebra (matrix maths) and scientific computing * Easy to use functions and syntax, deliberately similar to Matlab / Octave * Uses template meta-programming techniques to increase efficiency * Provides user-friendly wrappers for OpenBLAS, Intel MKL, LAPACK, ATLAS, ARPACK, SuperLU and FFTW libraries * Useful for machine learning, pattern recognition, signal processing, bioinformatics, statistics, finance, etc. * Downloads:... -
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zkcm
A C++ library for multiprecision complex-number matrix calculations.
zkcm library is a C++ library for multi-precision complex-number matrix calculations. It provides a number of functionalities including the LU decomposition, the singular value decomposition, tensor product calculation, tracing-out operations, etc. -
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Maestro Framework
A framework for Claude Opus to intelligently orchestrate subagents
...It can maintain context between subtasks so later steps can build on earlier work. The project can also generate exchange logs and save them as Markdown for review. Overall, it is useful for experimenting with multi-agent task decomposition, AI-assisted planning, and model orchestration workflows. -
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Modular Monolith with DDD
Full Modular Monolith application with Domain-Driven Design approach
This is a sample / starter architecture project for building a modular monolith application using Domain-Driven Design (DDD) principles in .NET. It aims to show how to structure a monolithic application into modules (bounded contexts), while preserving separation of concerns, maintainability, and scalability, without splitting into microservices. Showing the application of best practices and object-oriented programming principles. Presentation of some architectural considerations, decisions,... -
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Frevo
Frevo is probably the simplest tool for evolutionary design
FREVO is an open-source framework developed in Java to help engineers and scientists in evolutionary design or optimization tasks. The major feature of FREVO is the componentwise decomposition and separation of the key building blocks for each optimization tasks. We identify these as the problem definition, solution representation and the optimization method. This structure enables the components to be designed separately allowing the user to easily swap and evaluate different configurations and methods or to connect an external simulation tool. ... -
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AlphaTensor
AI discovers faster, efficient algorithms for matrix multiplication
AlphaTensor, developed by Google DeepMind, is the research codebase accompanying the 2022 Nature publication “Discovering faster matrix multiplication algorithms with reinforcement learning.” The project demonstrates how reinforcement learning can be used to automatically discover efficient algorithms for matrix multiplication — a fundamental operation in computer science and numerical computation. The repository is organized into four main components: algorithms, benchmarking,... -
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Replica Dataset
High-fidelity indoor 3D dataset for AI simulation and robotics
...Each environment contains detailed models of real-world spaces, including rooms, furniture, glass, and mirror surfaces. The dataset also provides semantic and instance segmentations, planar decomposition, and navigation meshes, making it highly suitable for simulation, visual perception, and autonomous navigation tasks. Replica integrates seamlessly with AI Habitat, Meta’s framework for embodied AI training, enabling large-scale agent simulation and photorealistic rendering for reinforcement learning and robotics. Researchers can use Replica’s ReplicaViewer to interactively explore the 3D scenes. -
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pure python polyfit
python2/3: compute polyfit (1D, 2D, N-D) without thirdparty libraries
python2/3: compute polyfit (1D, 2D, N-D) without any thirdparty library like numpy, scipy etc. also can be used for least squares solution computation and for A=QR matrix decomposition. Tested with python 2.7 and 3.4 Consider donating to this project: https://sourceforge.net/p/purepythonpolyfit/donation For a Sample use, refer to the WIKI -
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HRDAG
Framework for Hierarchical Graph Decomposition
This is a framework used to decompose hierarchical graphs, i.e.,graphs which were created from or contain a hierarchy of modules. Each module is reused several times in the hierarchy. This may be useful to reverse-engineer human constructs like electronic equipment, manufactured machines, or bureaucratic hierarchies; but also to decompose natural constructs like gene-relation or protein-relation nets. -
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CVM C++ Class Library encapsulates concepts of vector and square, band, symmetric and hermitian matrices in Euclidean space of real and complex numbers. It utilizes BLAS and LAPACK Fortran libraries. See http://cvmlib.com for binaries and more details.
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Fast Matrix for Java
General purpose matrix utilities for Java in Parallel Computing
Fast Matrix for Java (fm4j) is a general-purpose matrix utility library for computing with dense matrices. fm4j encapsulated different underlying implementations and select the optimal one in run-time depending on the size of the input matrix. Moreover, fm4j employs Java (Tm) Concurrency to take advantage of the computation power of multi-cor processors. -
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matrix.h
Some basic matrix algorithms implemented in C
This is a collection of some matrix algorithms like matrix inverse, LU decomposition, Gauss elimination, matrix multiplication, matrix pow, matrix add, matrix subtract etc. This package also contains debugging information for the above algorithms -
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Dantzig-Wolfe Solver
An implementation of Dantzig-Wolfe decomposition built upon GLPK
An implementation of Dantzig-Wolfe decomposition built upon the GNU Linear Programming Kit. This is a command line tool for solving properly decomposed linear programs. There are several examples and some documentation to guide the use of this solver. Forked over to GitHub (see link). -
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analyzematrix
Command line tool for reporting details on a given matrix
analyzematrix is a command line tool for learning detailed information about a matrix including its inverse, determinant, eigenvalues, eigenvectors, and singular value decomposition. -
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math toolkit
A C++ and Python library for finance, statistics and linear algebra.
...Statistics features include mean, median, variance, standard deviation, covariance, correlation, linear regression, probabilities and random variates of various distributions ... Linear algebra features include matrix arithmetic, inverse, determinant, rank, linear system solution, lu/qr decomposition, svd, eigen values/vectors ... And some auxiliary features like random number generators, equation solution, numerical integration, permutation/combination and gcd/lcm etc. It is aimed to be a convenient and handy toolkit to check out your ideas. -
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f2what
Lapack/quadprog QP for VBA/.Net/Java
...It offers a Fortran77 parser with code transformations, variable disambiguation, and modular output to other programming languages. It also offers already translated versions of Lapack and quadprog to Java, .Net and VBA, to give access to SVD, LU, QR, Cholesky, eigenvalue decomposition, linear system solving and QP optimization in those three languages. -
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open source PLM system - Product Structure management (BOM management) system and Electronic documents management or Entreprise Content Management (ECM) system
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HASEM
Matrix c++ library solving any linear algebra problems
HASEM is a c++ template library, it can be easily configure as a expression template. HASEM solves any linear equation of any kind, it might be homogenous/none homogenous, compute the inverse of square/none square matrices, find LU decomposition, find determinant and rank of matrices, calculate the characteristic polynomial of matrices, find the eigenvalues and eigen vectors and so on. HASEM uses many methods, therefore, you are not limited to just one method, you have the choice to define your desire method as default one. With over 200 member functions and over 40 none member functions HASEM is almost able to solve any linear algebra problems. ... -
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Simple order fulfillment system with flexible order decomposition and domain specific programming language for describing decomposition scenarios. Most suitable for Mobile Communications operators who are using Oracle BPEL and AIA technology.
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The NUMIPAD library implements several methods/algorithms to solve inverse problems and adaptive decomposition (i.e. Tikhonov regularization, Total Variation, Basis Pursuit, etc.)
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