Search Results for "sparse"
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Showing 33 open source projects for "sparse"
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Stop Storing Third-Party Tokens in Your DatabaseRolling your own OAuth token storage can be a security liability. Token Vault securely stores access and refresh tokens from federated providers and handles exchange and renewal automatically. Connected accounts, refresh exchange, and privileged worker flows included.
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MongoDB Atlas runs apps anywhereMongoDB Atlas gives you the freedom to build and run modern applications anywhere—across AWS, Azure, and Google Cloud. With global availability in over 115 regions, Atlas lets you deploy close to your users, meet compliance needs, and scale with confidence across any geography.
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SuiteSparse
The official SuiteSparse library: a suite of sparse matrix algorithms
The official SuiteSparse library: a suite of sparse matrix algorithms authored or co-authored by Tim Davis, Texas A&M University. -
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CasADi
CasADi is a symbolic framework for numeric optimization
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 in C++, Python, or Matlab/Octave. CasADi's backbone is a symbolic framework implementing forward and reverse modes of AD on expression graphs to construct gradients, large-and-sparse Jacobians, and Hessians. ... -
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go-datastructures
A collection of useful, performant, and threadsafe Go datastructures
...Bitarray used to detect existence without having to resort to hashing with hashmaps. Requires entities have a uint64 unique identifier. Two implementations exist, regular and sparse. Sparse saves a great deal of space but insertions are O(log n). There are some useful functions on the BitArray interface to detect intersection between two bitarrays. This package also includes bitmaps of length 32 and 64 that provide increased speed and O(1) for all operations by storing the bitmaps in unsigned integers rather than arrays. -
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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. Work on HYPRE began in the late 1990s. It has since been used by research... -
Ship Agents FasterGemini Enterprise Agent Platform lets you rapidly build, scale, govern and optimize production-ready agents grounded in your organization's data. The platform enables developers to build custom or pre-built agents for virtually any use case. New customers get $300 in free credits.
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DeepCTR
Package of deep-learning based CTR models
...It is compatible with both tf 1.x and tf 2.x. With the great success of deep learning,DNN-based techniques have been widely used in CTR prediction task. The data in CTR estimation task usually includes high sparse,high cardinality categorical features and some dense numerical features. Since DNN are good at handling dense numerical features,we usually map the sparse categorical features to dense numerical through embedding technique. -
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Vulcain
Fast and idiomatic client-driven REST APIs
...A reference, production-grade, implementation gateway server is also available in this repository. It's free software (AGPL) written in Go. A Docker image is provided. Current solutions for these problems (GraphQL, JSON:API's embedded resources and sparse fieldsets, etc.) are smart network hacks for HTTP/1. But these hacks come with (too) many drawbacks when it comes to HTTP cache, logs and even security. Fortunately, thanks to the new features introduced in HTTP/2, it's now possible to create true REST APIs fixing these problems with ease. -
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DeepCTR-Torch
Easy-to-use,Modular and Extendible package of deep-learning models
...With the great success of deep learning, DNN-based techniques have been widely used in CTR estimation tasks. The data in the CTR estimation task usually includes high sparse,high cardinality categorical features and some dense numerical features. Low-order Extractor learns feature interaction through product between vectors. Factorization-Machine and it’s variants are widely used to learn the low-order feature interaction. High-order Extractor learns feature combination through complex neural network functions like MLP, Cross Net, etc. -
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EnTT
A fast and reliable entity component system (ECS) and much more
...Statically generated integer identifiers for types (assigned either at compile-time or at runtime). A constexpr utility for human readable resource names. An incredibly fast entity-component system based on sparse sets, with its own pay for what you use policy to adjust performance and memory usage according to the users' requirements. Offers a minimal configuration system built using the monostate pattern. -
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MonoTorrent
The repository for MonoTorrent, a bittorrent library for .NET
This is a list of all the BEPs which have been implemented in MonoTorrent. A full list of all available BEPs can be seen. Prioritise specific files. Selective file downloading (including the ability to not download specific files). Rarest first piece picking (takes priorisation into account). End-game mode to boost the last 1-2% of the download. Sequential downloading (for media files). Per-torrent download/upload rate limiting. Overall download/upload rate limiting. In memory cache to... -
Stop Cyber Threats with VM-Series Next-Gen Firewall on AzureGain integrated visibility across all traffic in a single pass. Deploy Palo Alto Networks VM-Series to determine application identity and content while automating security policy updates via rich APIs.
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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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gopkg
Example for the go pkg's function
gopkg is a large community-driven repository of examples for Go’s standard library packages, created to fill the gap left by the relatively sparse official examples. The project organizes content so that each package has its own directory and each function within that package gets its own Markdown file with code examples. The idea is that developers can quickly look up “how do I actually use this function?” without digging through source code or scattered blog posts. The maintainer provides conventions for naming and formatting, and requires that submitted examples compile and run locally or on the Go Playground, which helps keep the collection reliable. ... -
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hloc
Visual localization made easy with hloc
...It's much simpler since a 3D SfM model is not needed. We show in pipeline_SfM.ipynb how to run 3D reconstruction for an unordered set of images. This generates reference poses, and a nice sparse 3D model suitable for localization with the same pipeline as Aachen. -
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MLPACK is a C++ machine learning library with emphasis on scalability, speed, and ease-of-use. Its aim is to make machine learning possible for novice users by means of a simple, consistent API, while simultaneously exploiting C++ language features to provide maximum performance and flexibility for expert users. * More info + downloads: https://mlpack.org * Git repo: https://github.com/mlpack/mlpack
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BitMagic Library
Compressed bit-sets, sparse bit matrices and algorithms
BitMagic - C and C++ library implementing dynamic bitvectors and bit-set algorithms with several types of on-the-fly, adaptive compression. Designed for use in databases, search systems, data-mining algorithms, scientific projects. The core of the library is C++, but it provides C-compatibility wrappers and can be compiled without C++ runtime. Optimizations for Intel SSE2, SSE4.2 and AVX2. -
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Style2Paints
Sketch + style = paints
style2paints is an AI-assisted colorization system aimed primarily at line art and manga, turning monochrome drawings into colored illustrations with minimal manual effort. It combines automatic color inference with user guidance, letting artists nudge the model using sparse color hints, masks, or style references. The pipeline focuses on preserving line quality while spreading coherent colors and shading across regions that are often ambiguous to purely automatic methods. Iterative refinement is a core workflow: you can add or adjust hints, rerun inference, and progressively converge on a desired palette and lighting. ... -
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LaMa
LaMa - A Localization and Mapping library
LaMa is a C++11 software library for robotic localization and mapping developed at the Intelligent Robotics and Systems (IRIS) Laboratory at the University of Aveiro - Portugal. It includes a framework for 3D volumetric grids (for mapping), a localization algorithm based on scan matching, and two SLAM solutions (an Online SLAM and a Particle Filter SLAM). The main feature is efficiency. Low computational effort and low memory usage whenever possible. The minimum viable computer to run our... -
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Minkowski Engine
Auto-diff neural network library for high-dimensional sparse tensors
The Minkowski Engine is an auto-differentiation library for sparse tensors. It supports all standard neural network layers such as convolution, pooling, unspooling, and broadcasting operations for sparse tensors. The Minkowski Engine supports various functions that can be built on a sparse tensor. We list a few popular network architectures and applications here. To run the examples, please install the package and run the command in the package root directory. ... -
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Sparse Attention
"Generating Long Sequences with Sparse Transformers" examples
Sparse Attention is OpenAI’s code release for the Sparse Transformer model, introduced in the paper Generating Long Sequences with Sparse Transformers. It explores how modifying the self-attention mechanism with sparse patterns can reduce the quadratic scaling of standard transformers, making it possible to model much longer sequences efficiently. -
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XIVO
X Inertial-aided Visual Odometry
...XIVO runs at 140FPS on stored data (here from a RealSense D435i sensor) or on live streams with a latency of around 1-7ms, depending on the hardware. It takes as input video frames from a calibrated camera and inertial measurements from an IMU and outputs a sparse point cloud with attribute features and 6 DOF pose of the camera. It performs auto-calibration of the relative pose between the camera and the IMU as well as the time-stamp alignment. -
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X-DeepLearning
An industrial deep learning framework for high-dimension sparse data
X-DeepLearning (XDL for short) is a complete set of deep optimization solutions for high-dimensional sparse data scenarios (such as advertising/recommendation/search, etc.). XDL version 1.2 has been released recently. Performance optimization for large batch/low concurrency scenarios, 50-100% performance improvement in such scenarios. Storage and communication optimization, parameters are automatically allocated globally without manual intervention, and requests are merged to completely eliminate computing/storage/communication hotspots of ps. ... -
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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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ViennaCL
Linear algebra and solver library using CUDA, OpenCL, and OpenMP
ViennaCL provides high level C++ interfaces for linear algebra routines on CPUs and GPUs using CUDA, OpenCL, and OpenMP. The focus is on generic implementations of iterative solvers often used for large linear systems and simple integration into existing projects. -
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Immutable Sparse Wave Trees (WaveTree)
Realtime bigdata tool for bit strings up to 2^63 based on AVL forest
...All those operations can be done millions of times per second regardless of size because the AVL forest reuses existing branches recursively. Theres a scalar (originally for copy/pasting subranges of sounds) and a bit Java package. Sparse n dimensional matrix. -
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The library for utilization of Minimal Quadtree format for storing very large sparse matrices. Please see the paper referenced below for the description of a problem. Corresponding papers: Tree-based Space Efficient Formats for Storing the Structure of Sparse Matrices (I. Šimeček, D. Langr, P. Tvrdík), In Scalable Computing: Practice and Experience, volume 15, 2014. Space Efficient Formats for Structure of Sparse Matrices Based on Tree Structures (I.
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Immutable Collections for Java
Immutable/Persistent Collections Library
...The library includes a singly linked (cons/cddr style) list/stack, an integer trie based indexed list, a 2-3 tree based random access indexed list, a 2-3 tree based map, a hash trie based map, and hash and tree based sets, and sparse arrays. All collections provide immutable Cursor as well as standard Iterator classes for looping through all elements. A utility class provides functional style algorithmic processing of Cursors including foldLeft, foldRight, collect, select, and reject. The 2-3 tree and integer trie classes are optimized for performance and can be used alongside java.util Collections when immutability is needed for safe data sharing.
