Search Results for "research" - Page 5
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Showing 2882 open source projects for "research"
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CoreNet
CoreNet: A library for training deep neural networks
...Its distributed runtime manages synchronization, load balancing, and mixed-precision computation to maximize throughput while minimizing communication bottlenecks. CoreNet integrates tightly with Apple’s proprietary ML stack and hardware, serving as the foundation for research in computer vision, language models, and multimodal systems within Apple AI. The framework includes monitoring tools, fault tolerance mechanisms, and efficient checkpointing for massive training runs. -
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Grey Wolf Optimizer for Path Planning
Grey Wolf Optimizer (GWO) path planning/trajectory
...Users can adjust objective function weights and experiment with multiple heuristic search strategies to explore optimal solutions. This project demonstrates applications in multi-agent and multi-UAV cooperative path planning, making it useful for research and educational purposes in the field of intelligent optimization and robotics. -
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Metarget
Framework for automatic construction of vulnerable infrastructures
Metarget = meta- + target, a framework providing automatic constructions of vulnerable infrastructures, used to deploy simple or complicated vulnerable cloud native targets swiftly and automatically. During security research, we might find that the deployment of a vulnerable environment often takes much time, while the time spent on testing PoC or ExP is comparatively short. In the field of cloud-native security, thanks to the complexity of cloud-native systems, this issue is more terrible. There are already some excellent security projects like Vulhub, and VulApps in the open-source community, which pack vulnerable scenes into container images so that researchers could utilize them and deploy scenes quickly. ... -
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OpenWPM
A web privacy measurement framework
OpenWPM is a web privacy measurement framework that makes it easy to collect data for privacy studies on a scale of thousands to millions of websites. OpenWPM is built on top of Firefox, with automation provided by Selenium. It includes several hooks for data collection. Check out the instrumentation section below for more details. OpenWPM is tested on Ubuntu 18.04 via TravisCI and is commonly used via the docker container that this repo builds, which is also based on Ubuntu. Although we... -
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RecBole
A unified, comprehensive and efficient recommendation library
...RecBole is developed based on Python and PyTorch for reproducing and developing recommendation algorithms in a unified, comprehensive and efficient framework for research purpose. It can be installed from pip, conda and source, and is easy to use. We have implemented more than 100 recommender system models, covering four common recommender system categories in RecBole and eight toolkits of RecBole2.0, including General Recommendation, Sequential Recommendation, Context-aware Recommendation, and Knowledge-based Recommendation and sub-packages. -
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DevSec Hardening
This Ansible collection provides battle tested hardening
...The project founders where tasked with the challenge to automate different security requirements of Deutsche Telekom for their infrastructure. Deutsche Telekom, T-Labs and Telekom Security funded the initial research and allowed the team to open source the automation. -
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rollama
Wrap the Ollama API, which allows you to run different LLMs
...It is designed to make LLM usage accessible to data scientists and researchers who work primarily in R, allowing them to generate text, analyze data, and create embeddings without relying on external cloud services. The package emphasizes reproducibility and privacy by enabling local execution of models, which is especially valuable for sensitive or research-oriented workflows. It supports common LLM tasks such as text generation, annotation, and embedding creation, making it useful for tasks like document analysis and data labeling. The design mirrors familiar R workflows, allowing users to integrate AI capabilities into scripts, notebooks, and data pipelines with minimal friction. ... -
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mgrep
A calm, CLI-native way to semantically grep everything, like code
...It also includes features such as background indexing to keep your search index up to date without interrupting your workflow and web search integration to expand the scope of queries beyond local files. Designed for both programmers and agents, it integrates naturally into development and research workflows while offering thoughtful defaults that keep output clean and informative. -
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Best-websites-a-programmer-should-visit
Some useful websites for programmers
Best-websites-a-programmer-should-visit is a living, community-curated directory of links that programmers consistently find useful throughout their careers. Rather than being a random bookmark dump, it organizes resources into practical categories such as algorithms, competitive programming, reading materials, podcasts, newsletters, interview prep, design, security, performance, and more. The list aims to reduce the “what should I learn next?” friction by pointing you to high-signal,... -
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Flax
Flax is a neural network library for JAX
...Flax emphasizes composability: optimizers, training loops, and checkpointing are provided as examples or utilities rather than monolithic frameworks, encouraging research-friendly customization. The library is widely used in vision, language, and reinforcement learning, often serving as a thin layer atop NumPy-like JAX primitives. Tutorials and examples show patterns for multi-host training, mixed precision, and advanced input pipelines that scale from laptops to TPUs. -
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Shumai
Fast Differentiable Tensor Library in JavaScript & TypeScript with Bun
Shumai is an experimental differentiable tensor library for TypeScript and JavaScript, developed by Facebook Research. It provides a high-performance framework for numerical computing and machine learning within modern JavaScript runtimes. Built on Bun and Flashlight, with ArrayFire as its numerical backend, Shumai brings GPU-accelerated tensor operations, automatic differentiation, and scientific computing tools directly to JavaScript developers. -
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GenAI Processors
GenAI Processors is a lightweight Python library
GenAI Processors is a lightweight Python library for building modular, asynchronous, and composable AI pipelines around Gemini. Its central abstraction is the Processor, a unit of work that consumes an asynchronous stream of parts (text, images, audio, JSON) and produces another stream, making it natural to chain operations and keep everything streaming end-to-end. Processors can be composed sequentially (to build multi-step flows) or in parallel (to fan-out work and merge results), which... -
13
K8tools
Security- and exploitation-oriented utilities and proof-of-concepts
K8tools is a large, curated GitHub repository collecting dozens (hundreds) of security- and exploitation-oriented utilities, proof-of-concepts, and payloads aimed at penetration testing, privilege escalation, and vulnerability exploitation. The project bundles exploits for many well-known CVEs, remote get-shell scripts, local privilege-escalation helpers, credential-harvesting utilities, scanning and brute-force tools, and a variety of platform-specific binaries and archives organized into... -
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EthereumJS Monorepo
Monorepo for the Ethereum VM TypeScript Implementation
...They are complemented by helper packages like RLP for data encoding/decoding or Util, providing helper functionalities like (byte) conversion, signatures, types and others. Finally, the EthereumJS Execution Client (EthereumJS) has been in active development for some time now. It already serves a variety of purposes like testing, research (e.g. EIPs) and developer tooling. -
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Opacus
Training PyTorch models with differential privacy
...Supports most types of PyTorch models and can be used with minimal modification to the original neural network. Open source, modular API for differential privacy research. Everyone is welcome to contribute. ML practitioners will find this to be a gentle introduction to training a model with differential privacy as it requires minimal code changes. Differential Privacy researchers will find this easy to experiment and tinker with, allowing them to focus on what matters. -
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Deepchecks
Test Suites for validating ML models & data
...Deepchecks accompany you through various validation and testing needs such as verifying your data’s integrity, inspecting its distributions, validating data splits, evaluating your model and comparing between different models. While you’re in the research phase, and want to validate your data, find potential methodological problems, and/or validate your model and evaluate it. To run a specific single check, all you need to do is import it and then to run it with the required (check-dependent) input parameters. More details about the existing checks and the parameters they can receive can be found in our API Reference. ... -
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Haiku
JAX-based neural network library
Haiku is a library built on top of JAX designed to provide simple, composable abstractions for machine learning research. Haiku is a simple neural network library for JAX that enables users to use familiar object-oriented programming models while allowing full access to JAX’s pure function transformations. Haiku is designed to make the common things we do such as managing model parameters and other model state simpler and similar in spirit to the Sonnet library that has been widely used across DeepMind. ... -
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Open LLMs
A list of open LLMs available for commercial use
Open LLMs, by the same author behind applied-ml — serves as a curated directory of open large language models (LLMs) that are available for commercial or open-source use. Rather than proprietary or closed-source LLMs, this repo focuses on freely available or permissively licensed models that practitioners can download, run, fine-tune or integrate without restrictive licensing. For teams or developers interested in experimenting with LLMs but wanting to avoid vendor lock-in or licensing... -
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XiangShan
Open-source high-performance RISC-V processor
...The design targets modern performance goals—deep pipelines, speculative execution, multi-issue decode/execute, and sophisticated branch prediction—while remaining synthesizable for ASIC flows and portable to FPGAs for research. A modular microarchitecture separates frontend, backend, and memory subsystems with coherent caches and scalable interconnects, enabling multi-core configurations. The project invests heavily in verification: differential testing against reference models, extensive random instruction tests, and full software stacks (bootloaders, Linux) to validate correctness under realistic workloads. ... -
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satellite-image-deep-learning
Resources for deep learning with satellite & aerial imagery
...Note there is a huge volume of academic literature published on these topics, and this repository does not seek to index them all but rather list approachable resources with published code that will benefit both the research and developer communities. If you find this work useful please give it a star and consider sponsoring it. You can also follow me on Twitter and LinkedIn where I aim to post frequent updates on my new discoveries, and I have created a dedicated group on LinkedIn. I have also started a blog here and have published a post on the history of this repository called Dissecting the satellite-image-deep-learning repo. -
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Formik
Build forms in React
Formik is the world's most popular open-source form library for React and React Native. Formik takes care of the repetitive and annoying stuff, keeping track of values/errors/visited fields, orchestrating validation, and handling submission, so you don't have to. This means you spend less time wiring up state and change handlers and more time focusing on your business logic. No fancy subscriptions or observables under the hood, just plain React state and props. By staying within the core... -
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Open MCT
A web based mission control framework
...Web-based, for desktop and mobile. Software based on Open MCT is in use as a data visualization tool in support of multiple missions at the Jet Propulsion Laboratory, and at NASA's Ames Research Center to support the development of lunar rover mission concepts. Open MCT can be adapted for planning and operations of any system that produces telemetry. While Open MCT is developed to support space missions, its core concepts are not unique to that domain. It can display streaming and historical data, imagery, timelines, procedures, and other data visualizations, all in one place. ... -
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Unified Communication X
Communication framework for data-centric high-performance applications
Accelerate Your Network Performance with UCX. Collaboration between industry, laboratories, and academia to create an open-source, production-grade communication framework for data-centric and high-performance applications. Unified Communication X (UCX) is an award winning, optimized production proven communication framework for modern, high-bandwidth and low-latency networks. UCX exposes a set of abstract communication primitives which utilize the best of available hardware resources and... -
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Groq Python
The official Python Library for the Groq API
...The SDK handles authentication (via environment variable or parameter), defines proper type-safe request/response data types, and supports both synchronous and asynchronous usage patterns depending on your application needs. This makes it easy to integrate Groq-powered AI capabilities into backend services, data pipelines, research notebooks, or applications written in Python. For those building AI-based tooling, automation scripts, or ML-backed backends, groq-python abstracts away HTTP request plumbing and exposes a clean API, accelerating development and reducing boilerplate. -
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FairChem
FAIR Chemistry's library of machine learning methods for chemistry
...Version 2 modernizes the stack with a cleaner core package and breaking changes relative to V1, focusing on simpler installs and a stable API surface for production and research. The centerpiece models (e.g., UMA variants) plug directly into the ASE ecosystem via a FAIRChem calculator, so users can run relaxations, molecular dynamics, spin-state energetics, and surface catalysis workflows with the same pretrained network by switching a task flag. Tasks span heterogeneous domains—catalysis (OC20-style), inorganic materials (OMat), molecules (OMol), MOFs (ODAC), and molecular crystals (OMC)—allowing one model family to serve many simulations. ...
