Search Results for "sparse" - Page 4
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Showing 180 open source projects for "sparse"
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DALL-E in Pytorch
Implementation / replication of DALL-E, OpenAI's Text to Image
Implementation / replication of DALL-E (paper), OpenAI's Text to Image Transformer, in Pytorch. It will also contain CLIP for ranking the generations. Kobiso, a research engineer from Naver, has trained on the CUB200 dataset here, using full and deepspeed sparse attention. You can also skip the training of the VAE altogether, using the pretrained model released by OpenAI! The wrapper class should take care of downloading and caching the model for you auto-magically. You can also use the pretrained VAE offered by the authors of Taming Transformers! Currently only the VAE with a codebook size of 1024 is offered, with the hope that it may train a little faster than OpenAI's, which has a size of 8192. ... -
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TensorFlow Ranking
Learning to rank in TensorFlow
...We provide a demo, with no installation required, to get started on using TF-Ranking. This demo runs on a colaboratory notebook, an interactive Python environment. Using sparse features and embeddings in TF-Ranking. -
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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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DiffEqOperators.jl
Linear operators for discretizations of differential equations
...Care is taken to give efficiency by avoiding unnecessary allocations, using purpose-built stencil compilers, allowing GPUs and parallelism, etc. Any operator can be concretized as an Array, a BandedMatrix or a sparse matrix. -
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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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FUNseq
Cell segmentation/tracking for determing aggresive cancer phenotypes
This page shows the cell segmentation/tracking program for FUNseq pipeline. Identifying a sparse subset of cancer cells from a large heterogeneous population, based on aggressive phenotypes (like invasive migration, multipolar divisions, or asymmetric lineage development) is challenging. Also, such aberration identification is critical, as cells exhibiting these characteristics are linearly correlated with poor prognosis. A high-throughput screening microscope has been developed in our group to capture these sparse, abnormal cancer cells. ... -
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AugmentedGaussianProcesses.jl
Gaussian Process package based on data augmentation, and sparsity
AugmentedGaussianProcesses.jl is a Julia package in development for Data Augmented Sparse Gaussian Processes. It contains a collection of models for different gaussian and non-gaussian likelihoods, which are transformed via data augmentation into conditionally conjugate likelihood allowing for extremely fast inference via block coordinate updates. There are also more options to use more traditional variational inference via quadrature or Monte Carlo integration. -
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fastPTOptimizer
a fork of the Panorama Tools / libpano13 with a fast PTOptimizer
...This is possible by exploiting the sparseness of the mathematical optimization problem. The original PTOptimizer uses the well proven Levenberg Marquardt optimizer lmdif from the minpack software. fastPTOptimizer uses a "sparse" optimizer lmdif_sparse that uses the SuiteSparse library. -
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lightning library
Large-scale linear classification, regression and ranking in Python
lightning is a library for large-scale linear classification, regression and ranking in Python. -
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ddarch
Linux helper tool to easily create, preserve and restore disk images
ddarch is a simple helper tool that wraps dd, fdisk, parted along with other utilities to easily create, preserve and restore disk images. When sparse files are not in play, dd leaves you with an image equal in size to the size of the input media. Such an image may contain empty spaces, unpartitioned volumes, and be cumbersome to compress and store. Restoring an image to a device of a different size may also require appropriate modifications to the image (partition resizing, trimming) or the device itself after the restore (enlarging the last partition). ... -
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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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JSONAPI
jsonapi.org style payload serializer and deserializer
...The library favors explicit schemas and type-safe bindings where possible, which helps large teams avoid drift in field names and relationship structures. It also offers utilities for sparse fieldsets and compound documents, minimizing payload size while keeping related entities synchronized. With consistent error objects and status mapping, it makes API error handling uniform across clients. -
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Objectron
A dataset of short, object-centric video clips
The Objectron dataset is a collection of short, object-centric video clips, which are accompanied by AR session metadata that includes camera poses, sparse point-clouds and characterization of the planar surfaces in the surrounding environment. In each video, the camera moves around the object, capturing it from different angles. The data also contain manually annotated 3D bounding boxes for each object, which describe the object’s position, orientation, and dimensions. The dataset consists of 15K annotated video clips supplemented with over 4M annotated images in the following categories: bikes, books, bottles, cameras, cereal boxes, chairs, cups, laptops, and shoes. ... -
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FDMNES powered by sparse solvers
The sources and builds history of FDMNES project
The sources and builds history of FDMNES project (http://neel.cnrs.fr/spip.php?rubrique1007&lang=en ) with parallel sparse solvers moved to github: https://github.com/gudasergey/fdmnes -
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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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A symbolic framework for C++, Python and Octave implementing automatic differentiation by source code transformation in forward and reverse modes on sparse matrix-valued computational graphs.
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xLearn
High performance, easy-to-use, and scalable machine learning (ML)
xLearn is a high-performance, easy-to-use, and scalable machine learning package that contains linear model (LR), factorization machines (FM), and field-aware factorization machines (FFM), all of which can be used to solve large-scale machine learning problems. xLearn is especially useful for solving machine learning problems on large-scale sparse data. Many real-world datasets deal with high dimensional sparse feature vectors like a recommendation system where the number of categories and users is on the order of millions. In that case, if you are a user of liblinear, libfm, and libffm, now xLearn is another better choice. -
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The project is a continuation of the old dupmerge program. dupmerge securely searches for files (of size >0) with equal content and if it finds such files, they get hard linked for saving disk space. It also has a sparse mode, a deletion mode and an
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Tera
An Internet-scale database
...Besides, Tera is widely used in many Baidu products with varied demands， which range from throughput-oriented applications to latency-sensitive services, including web indexing, WebPage DB, LinkBase DB, etc. Tera is the collection of many sparse, distributed, multidimensional tables. The table is indexed by a row key, column key, and a timestamp; each value in the table is an uninterpreted array of bytes. Support RAMDISK/SSD/DFS tiered cache. Block cache and Bloom Filters for real-time queries. Multi-type table support (RAMDISK/SSD/DISK table). Easy to use C++/Java/Python/REST-ful API. ... -
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RND
Random data generator: secure character streams and large files
Generate a lot of random junk. Create: • huge files • random character stream • specific character sequence Example uses - generate: • specific number of characters for testing web forms • restricted range character stream • control characters, 'high characters', emojis for fuzzing application input • specific byte sequence • Unicode character range • file overwrites to the exact byte count • custom text strings as content filler • long password strings • specific...
