Search Results for "linear"
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38 projects for "linear" with 2 filters applied:
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GLM.jl
Generalized linear models in Julia
GLM.jl is a Julia package for fitting linear and generalized linear models (GLMs) with a syntax and functionality familiar to users of R or other statistical environments. It is part of the JuliaStats ecosystem and is tightly integrated with StatsModels.jl for formula handling, and Distributions.jl for specifying error families. The package supports modeling through both formula-based (e.g. -
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Peroxide
Rust numeric library with high performance and friendly syntax
Rust numeric library contains linear algebra, numerical analysis, statistics and machine learning tools with R, MATLAB, Python-like macros. Peroxide uses a 1D data structure to represent matrices, making it straightforward to integrate with BLAS (Basic Linear Algebra Subprograms). This means that Peroxide can guarantee excellent performance for linear algebraic computations by leveraging the optimized routines provided by BLAS. -
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HYPRE
Parallel solvers for sparse linear systems featuring multigrid methods
Livermore’s HYPRE library of linear solvers makes possible larger, more detailed simulations by solving problems faster than traditional methods at large scales. It offers a comprehensive suite of scalable solvers for large-scale scientific simulation, featuring parallel multigrid methods for both structured and unstructured grid problems. The HYPRE library is highly portable and supports a number of languages. -
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MathPHP
Powerful modern math library for PHP
Math PHP is a library that brings advanced mathematical functions and data analysis capabilities to PHP applications. It covers a wide range of topics, including linear algebra, calculus, statistics, probability, and numerical analysis. Math PHP is designed for developers and data scientists who require precise and efficient mathematical computations in PHP, making it suitable for scientific computing and data processing. -
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Agrona
High Performance data structures and utility methods for Java
Agrona provides a library of data structures and utility methods that are a common need when building high-performance applications in Java. Many of these utilities are used in the Aeron efficient reliable UDP unicast, multicast, and IPC message transport and provides high-performance buffer implementations to support the Simple Binary Encoding Message Codec. -
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NetTopologySuite
A .NET GIS solution that is fast and reliable for the .NET platform.
...NetTopologySuite is a direct port of all the functionalities offered by JTS Topology Suite: NTS exposes JTS in a '.NET way', for example using Properties, Indexers, etc. The JTS Topology Suite is an API for modeling and manipulating 2-dimensional linear geometry. It provides numerous geometric predicates and functions. JTS conforms to the Simple Features Specification for SQL published by the Open GIS Consortium. -
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Measurements.jl
Error propagation calculator and library for physical measurements
...Measurements.jl relieves you from the hassle of propagating uncertainties coming from physical measurements, when performing mathematical operations involving them. The linear error propagation theory is employed to propagate the errors. -
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Hasktorch
Tensors and neural networks in Haskell
Hasktorch is a powerful Haskell library for tensor computation and neural network modeling, built on top of libtorch (the backend of PyTorch). It brings differentiable programming, automatic differentiation, and efficient tensor operations into Haskell’s strongly typed functional paradigm. This project is in active development, so expect changes to the library API as it evolves. We would like to invite new users to join our Hasktorch discord space for questions and discussions.... -
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Dlib is a C++ toolkit containing machine learning algorithms and tools for creating complex software in C++ to solve real world problems.
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C++ Library of Abstract Algebra concepts and arithmetic algorithms defined in terms of these concepts, using Instigate Generic Programming Methodology. Based on this library we plan to develop Linear Algebra and Optimization concepts and algorithms.
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SigPack
SigPack - A signal processing library using Armadillo
SigPack is a C++ signal processing library using the Armadillo library as a base. The API will be familiar for those who has used IT++ and Octave/Matlab. -
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ALEPH-w
Data structures and Algorithms library
...It contains the main data structures: single and double lists, special arrays (dynamic and of bits), many types of trees: multitrees, binary search trees, avl, red-black, randomized, treaps, splay and other interesting types. Several types of hash tables are implemented: separated chaining, open adressing with linear probing and double function hash; this last one has a garbage colector mechanism that allows to free deleted entries. Dynamic linear hash tables are implemented too. The main algorithms on graphs are implemented in an easy way and with good performance features. Network Flow (maximum and min cost), cut points, topological sort, spanning trees, min paths. etc. ... -
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glslmath
C++ header-only library that simulates GLSL math
GLSLmath provides C++ math operations as defined by GLSL. For example, it provides methods to easily setup viewing transformations and perspective projections. GLSLmath has been inspired by the glm and slmath libraries, which aim to mimic GLSL, but in contrast to those GLSLmath does not focus on a complete conforming implementation of GLSL. It rather aims to provide a convenient single header file that implements the most commonly used subset of GLSL so that it is easy to use for rapid... -
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Neural Tangents
Fast and Easy Infinite Neural Networks in Python
...The library closely mirrors JAX’s stax API while extending it to return a kernel_fn alongside init_fn and apply_fn, enabling drop-in workflows for kernel computation. Kernel evaluation is highly optimized for speed and memory, and computations can be automatically distributed across accelerators with near-linear scaling. -
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Bootstrap.jl
Statistical bootstrapping library for Julia
Bootstrapping is a widely applicable technique for statistical estimation. -
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iJEPA
Official codebase for I-JEPA
...A context encoder sees visible regions of an image and predicts target embeddings for masked regions produced by a slowly updated target encoder, focusing learning on semantics instead of texture. This objective sidesteps generative pixel losses and avoids heavy negative sampling, producing features that transfer strongly with linear probes and minimal fine-tuning. The design scales naturally with Vision Transformer backbones and flexible masking strategies, and it trains stably at large batch sizes. i-JEPA’s predictions are made in embedding space, which is computationally efficient and better aligned with downstream discrimination tasks. The repository provides training recipes, data pipelines, and evaluation code that clarify which masking patterns and architectural choices matter most. -
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Alpa
Training and serving large-scale neural networks
Alpa is a system for training and serving large-scale neural networks. Scaling neural networks to hundreds of billions of parameters has enabled dramatic breakthroughs such as GPT-3, but training and serving these large-scale neural networks require complicated distributed system techniques. Alpa aims to automate large-scale distributed training and serving with just a few lines of code. -
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SimpleXlsxWriter
C++ library for creating XLSX files for MS Excel 2007 and above.
This library represents XLSX files writer for Microsoft Excel 2007 and above. The main feature of this library is that it uses C++ standard file streams. On the one hand it results in almost unnoticeable memory and CPU resources consumption while processing (that may be very useful at saving a large data arrays), but on the other hand it makes unfeasible to edit data that were written. Hence, if using this library the structure of the future report should be known enough. The library... -
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Harmonica
A simple, physics-based animation library
...It provides tools for creating smooth, natural motion in 2D and 3D applications. The project includes spring animation behavior that can make interface movement feel more organic than fixed linear transitions. It also includes projectile-style simulation that is useful for particles, motion effects, and game-like interactions. Harmonica can be used with terminal interfaces, Bubble Tea applications, and graphical projects that need realistic movement. Its main value is giving Go developers a small, efficient way to add physically inspired animation without building the math from scratch. -
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libRSF
A robust sensor fusion library for online localization
...The general idea of factor graphs is to describe the state estimation problem as a graph of nodes (the state variables) that are connected by factors (measurements). The resulting graph optimization problem can be solved by applying non-linear least squares optimization. -
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GtkDatabox
A GTK+-3 widget to display data
GtkDatabox is a widget for live display of large amounts of fluctuating numerical data. Data presentation (e.g. on linear or logarithmic scales, as dots or lines, with markers/labels) as well as user interaction (e.g. measuring distances) is easy. -
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Konbu Check
Linear constraint feasibility check and get program.
This program aims to check and gain a inner point from multiple set of linear constraints. This software works better in the case that range of variables are known and parameters are configured so. C++ and Eigen library needed, and to calculate more accurate, we may need mpfr++ library or, QD library. Freezed. -
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Tensor Algebra Compiler
The Tensor Algebra Compiler (taco) computes sparse tensor expressions
A fast and versatile compiler-based library for sparse linear and tensor algebra. TACO can be used to implement sparse linear and tensor algebra applications in a wide range of domains. TACO supports a wide range of sparse (and dense) linear/tensor algebra computations, from simpler ones like sparse matrix-vector multiplication to more complex ones like MTTKRP on higher-order sparse tensors. -
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Functional, Data Science Intro To Python
[tutorial]A functional, Data Science focused introduction to Python
...The assumption is a someone with zero experience in programming can follow this tutorial and learn Python with the smallest amount of information possible. The sections after that, involve varying levels of difficulty and cover topics as diverse as Machine Learning, Linear Optimization, build systems, command line tools, recommendation engines, Sentiment Analysis and Cloud Computing. -
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Tiramisu
Polyhedral compiler for expressing fast and portable data algorithms
...It provides a simple C++ API for expressing algorithms (Tiramisu expressions) and how these algorithms should be optimized by the compiler. Tiramisu can be used in areas such as linear and tensor algebra, deep learning, image processing, stencil computations and machine learning. The Tiramisu compiler is based on the polyhedral model thus it can express a large set of loop optimizations and data layout transformations. Currently, it targets (1) multicore X86 CPUs, (2) Nvidia GPUs, (3) Xilinx FPGAs (Vivado HLS) and (4) distributed machines (using MPI). ...
