Search Results for "algorithm" - Page 2
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Showing 2045 open source projects for "algorithm"
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Grafana: The open and composable observability platformGrafana is the open source analytics & monitoring solution for every database.
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jekyll-tagging-related_posts
Jekyll `related_posts` function based on tags
Jekyll related_posts function based on tags (works on Jekyll3). It replaces the original Jekyll's related_posts function to use tags to calculate relationships. The calculation algorithm is based on related_posts-jekyll_plugin. -
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Real-ESRGAN GUI
Cross-platform GUI for image upscaler Real-ESRGAN
...Real-ESRGAN can only enlarge the input image with a fixed 2-4x magnification (related to the selected model). This functionality is achieved by downsampling using a conventional scaling algorithm after multiple calls to Real-ESRGAN. Split each frame of the GIF and record the duration, zoom in one by one and then merge. Drag an image file or directory to any position in the window, and its path can be automatically set as the input. -
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nghttp2
HTTP/2 C Library and tools
nghttp2 is an implementation of HTTP/2 and its header compression algorithm HPACK in C. The framing layer of HTTP/2 is implemented as a form of reusable C library. On top of that, we have implemented HTTP/2 client, server and proxy. We have also developed a load test and benchmarking tool for HTTP/2. We have participated in httpbis working group since HTTP/2 draft-04, which is the first implementation draft. -
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R1-V
Witness the aha moment of VLM with less than $3
R1-V is an initiative aimed at enhancing the generalization capabilities of Vision-Language Models (VLMs) through Reinforcement Learning in Visual Reasoning (RLVR). The project focuses on building a comprehensive framework that emphasizes algorithm enhancement, efficiency optimization, and task diversity to achieve general vision-language intelligence and visual/GUI agents. The team's long-term goal is to contribute impactful open-source research in this domain. -
Gen AI apps are built with MongoDB AtlasMongoDB Atlas provides built-in vector search and a flexible document model so developers can build, scale, and run gen AI apps without stitching together multiple databases. From LLM integration to semantic search, Atlas simplifies your AI architecture—and it’s free to get started.
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openTSNE
Extensible, parallel implementations of t-SNE
openTSNE is a modular Python implementation of t-Distributed Stochasitc Neighbor Embedding (t-SNE) [1], a popular dimensionality-reduction algorithm for visualizing high-dimensional data sets. openTSNE incorporates the latest improvements to the t-SNE algorithm, including the ability to add new data points to existing embeddings [2], massive speed improvements [3] [4] [5], enabling t-SNE to scale to millions of data points, and various tricks to improve the global alignment of the resulting visualizations. -
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WAFW00F
WAFW00F allows one to identify and fingerprint Web App Firewall
...If that is not successful, it sends a number of (potentially malicious) HTTP requests and uses simple logic to deduce which WAF it is. If that is also not successful, it analyses the responses previously returned and uses another simple algorithm to guess if a WAF or security solution is actively responding to our attacks. For further details, check out the source code on our main repository. -
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Coluna.jl
Branch-and-Price-and-Cut in Julia
...Then, Coluna reformulates the original MIP and optimizes the reformulation using the algorithms you choose. Coluna aims to be very modular and tweakable so that you can define the behavior of your customized branch-and-price-and-cut algorithm. -
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Homemade Machine Learning
Python examples of popular machine learning algorithms
homemade-machine-learning is a repository by Oleksii Trekhleb containing Python implementations of classic machine-learning algorithms done “from scratch”, meaning you don’t rely heavily on high-level libraries but instead write the logic yourself to deepen understanding. Each algorithm is accompanied by mathematical explanations, visualizations (often via Jupyter notebooks), and interactive demos so you can tweak parameters, data, and observe outcomes in real time. The purpose is pedagogical: you’ll see linear regression, logistic regression, k-means clustering, neural nets, decision trees, etc., built in Python using fundamentals like NumPy and Matplotlib, not hidden behind API calls. ... -
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MCScanX
MCScanX: Multiple Collinearity Scan toolkit X version
MCScanX is a toolkit for detecting gene synteny and collinearity, aiding in the evolutionary analysis of gene arrangements across multiple genomes. It extends the original MCScan algorithm by incorporating additional utilities for visualization and downstream analyses. -
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SOFAJRaft
A production-grade java implementation of RAFT consensus algorithm
SOFAJRaft is a production-level, high-performance Java implementation based on the RAFT consistency algorithm that supports MULTI-RAFT-GROUP for high-load, low-latency scenarios. With SOFAJRaft you can focus on your business area. SOFAJRaft handles all RAFT-related technical challenges. SOFAJRaft is very user-friendly, which provides several examples, making it easy to understand and use. -
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TextDistance
Compute distance between sequences
...For main algorithms, text distance try to call known external libraries (fastest first) if available (installed in your system) and possible (this implementation can compare this type of sequences). Install text distance with extras for this feature. Textdistance use benchmark results for algorithm optimization and try to call the fastest external lib first (if possible). TextDistance show benchmarks results table for your system and saves libraries priorities into the libraries.json file in TextDistance's folder. This file will be used by text distance for calling the fastest algorithm implementation. Default libraries.json is already included in the package. -
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AReal
Lightning-Fast RL for LLM Reasoning and Agents. Made Simple & Flexible
...It is intended to facilitate reproducible RL training on reasoning / agentic tasks, supporting scaling from single nodes to large GPU clusters. It can streamline the development of AI agents and reasoning systems. Support for algorithm and system co-design optimizations (to improve efficiency and stability). -
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SHAP
A game theoretic approach to explain the output of ml models
...It connects optimal credit allocation with local explanations using the classic Shapley values from game theory and their related extensions. While SHAP can explain the output of any machine learning model, we have developed a high-speed exact algorithm for tree ensemble methods. Fast C++ implementations are supported for XGBoost, LightGBM, CatBoost, scikit-learn and pyspark tree models. To understand how a single feature effects the output of the model we can plot the SHAP value of that feature vs. the value of the feature for all the examples in a dataset. Since SHAP values represent a feature's responsibility for a change in the model output, the plot below represents the change in predicted house price as RM (the average number of rooms per house in an area) changes. -
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Yao
Extensible, Efficient Quantum Algorithm Design for Humans
...Its CUDA backend and batched quantum register support can make typical quantum circuits even faster. Yao is designed to be extensible. Its hierarchical architecture allows you to extend the framework to support and share your new algorithm and hardware. -
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Qdrant
Vector Database for the next generation of AI applications
...Alternatively, utilize ready-made client for Python or other programming languages with additional functionality. Implement a unique custom modification of the HNSW algorithm for the Approximate Nearest Neighbor Search. Search with a State-of-the-Art speed and apply search filters without compromising on results. Support additional payload associated with vectors. Not only stores payload but also allows filter results based on payload values. Unlike Elasticsearch post-filtering, Qdrant guarantees all relevant vectors are retrieved. -
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NonlinearSolve.jl
High-performance and differentiation-enabled nonlinear solvers
...The package includes its own high-performance nonlinear solvers which include the ability to swap out to fast direct and iterative linear solvers, along with the ability to use sparse automatic differentiation for Jacobian construction and Jacobian-vector products. NonlinearSolve.jl interfaces with other packages of the Julia ecosystem to make it easy to test alternative solver packages and pass small types to control algorithm swapping. It also interfaces with the ModelingToolkit.jl world of symbolic modeling to allow for automatically generating high-performance code. -
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Wesh Network Toolkit
Async Mesh Network Protocol for Extreme Communication
...Wesh Protocol provides end-to-end encryption and perfect forward secrecy for all the exchanged messages. Distributed p2p transmissions and hosting over IPFS powered by CRDT algorithm. Efficient end-to-end encryption and perfect forward secrecy to prevent eavesdropping and provide reliable identity access management. Distributed authentication and authorization. Multiple devices per identity. Resilient p2p transmissions between groups of mutually-authorized users. Improved performance and availability with decentralized rendez-vous servers. -
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GmSSL
Password toolbox that supports national secret
...GmSSL 3.0 greatly reduces memory requirements and binary code volume, does not rely on dynamic memory, and can be used in low-power embedded environments (MCU, SOC, etc.) National secret algorithm and SSL protocol are embedded in existing projects. The default CMake build system can be easily used with default compilation tools such as Visual Studio and Android NDK. Developers can also manually write Makefiles to compile in special environments, tailoring. -
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EPLB
Expert Parallelism Load Balancer
EPLB is DeepSeek’s open implementation of a load balancing algorithm designed for expert parallelism (EP) settings in MoE architectures. In EP, different “experts” are mapped to different GPUs or nodes, so load imbalance becomes a performance bottleneck if certain experts are invoked much more often. EPLB solves this by duplicating heavily used experts (redundancy) and then placing those duplicates across GPUs to even out computational load. -
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DualPipe
A bidirectional pipeline parallelism algorithm
DualPipe is a bidirectional pipeline parallelism algorithm open-sourced by DeepSeek, introduced in their DeepSeek-V3 technical framework. The main goal of DualPipe is to maximize overlap between computation and communication phases during distributed training, thus reducing idle GPU time (i.e. “pipeline bubbles”) and improving cluster efficiency. Traditional pipeline parallelism methods (e.g. 1F1B or staggered pipelining) leave gaps because forward and backward phases can’t fully overlap with communication. ... -
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Monero P2Pool
Decentralized pool for Monero mining
Decentralized pool for Monero mining. No central server that can be shutdown/blocked. P2Pool uses a separate blockchain to merge mine with Monero. Pool admin can't go rogue or be pressured to do an attack on the network because there is no pool admin. -
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Vowpal Wabbit
Machine learning system which pushes the frontier of machine learning
...There is a specific focus on reinforcement learning with several contextual bandit algorithms implemented and the online nature lending to the problem well. Vowpal Wabbit is a destination for implementing and maturing state-of-the-art algorithms with performance in mind. The input format for the learning algorithm is substantially more flexible than might be expected. Examples can have features consisting of free-form text, which is interpreted in a bag-of-words way. There can even be multiple sets of free-form text in different namespaces. Similar to the few other online algorithm implementations out there. There are several optimization algorithms available with the baseline being sparse gradient descent (GD) on a loss function. -
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Clustering.jl
A Julia package for data clustering
Methods for data clustering and evaluation of clustering quality. -
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etcd
Distributed reliable key-value store for the most critical data
A distributed, reliable key-value store for the most critical data of a distributed system. etcd is a strongly consistent, distributed key-value store that provides a reliable way to store data that needs to be accessed by a distributed system or cluster of machines. It gracefully handles leader elections during network partitions and can tolerate machine failure, even in the leader node. etcd is a consistent distributed key-value store. Mainly used as a separate coordination service, in... -
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MiniSom
MiniSom is a minimalistic implementation of the Self Organizing Maps
...Minisom is designed to allow researchers to easily build on top of it and to give students the ability to quickly grasp its details. The project initially aimed for a minimalistic implementation of the Self-Organizing Map (SOM) algorithm, focusing on simplicity in features, dependencies, and code style. Although it has expanded in terms of features, it remains minimalistic by relying only on the numpy library and emphasizing vectorization in coding style.
