Search Results for "design analysis algorithm"
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Showing 75 open source projects for "design analysis algorithm"
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Real-ESRGAN GUI
Cross-platform GUI for image upscaler Real-ESRGAN
The graphic interface of Real-ESRGAN, a practical and beautiful image magnification tool, refers to the design of waifu2x-caffe. This program is a graphical interface of Real-ESRGAN's command line program Real-ESRGAN-ncnn-vulkan , written in Python and tkinter, and supports Windows, Ubuntu and macOS platforms. According to actual measurements, arm64the single-architecture performance is better than universal2the dual- architecture Mac on the Apple chip, so Apple chip users are advised to pack... -
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Orange Data Mining
Orange: Interactive data analysis
Open source machine learning and data visualization. Build data analysis workflows visually, with a large, diverse toolbox. Perform simple data analysis with clever data visualization. Explore statistical distributions, box plots and scatter plots, or dive deeper with decision trees, hierarchical clustering, heatmaps, MDS and linear projections. Even your multidimensional data can become sensible in 2D, especially with clever attribute ranking and selections. Interactive data exploration... -
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Lama Cleaner
Image inpainting tool powered by SOTA AI Model
... their work. Completely free and open-source, fully self-hosted, supports CPU & GPU. Windows 1-Click Installer, classical image inpainting algorithm powered by cv2. Multiple SOTA AI models, and various inpainting strategies. Run as a desktop application. Interactive Segmentation on any object. -
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BioNeMo
BioNeMo Framework: For building and adapting AI models
BioNeMo is an AI-powered framework developed by NVIDIA for protein and molecular generation using deep learning models. It provides researchers and developers with tools to design, analyze, and optimize biological molecules, aiding in drug discovery and synthetic biology applications. -
Build Securely on Azure with Proven FrameworksMoving to the cloud brings new challenges. How can you manage a larger attack surface while ensuring great network performance? Turn to Fortinet’s Tested Reference Architectures, blueprints for designing and securing cloud environments built by cybersecurity experts. Learn more and explore use cases in this white paper.
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Super-Linter
Combination of multiple linters to install as a GitHub Action
This repository is for the GitHub Action to run a Super-Linter. It is a simple combination of various linters, written in bash, to help validate your source code. The super-linter finds issues and reports them to the console output. Fixes are suggested in the console output but not automatically fixed, and a status check will show up as failed on the pull request. The design of the Super-Linter is currently to allow linting to occur in GitHub Actions as a part of continuous integration... -
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TorchQuantum
A PyTorch-based framework for Quantum Classical Simulation
A PyTorch-based framework for Quantum Classical Simulation, Quantum Machine Learning, Quantum Neural Networks, Parameterized Quantum Circuits with support for easy deployments on real quantum computers. Researchers on quantum algorithm design, parameterized quantum circuit training, quantum optimal control, quantum machine learning, and quantum neural networks. Dynamic computation graph, automatic gradient computation, fast GPU support, batch model terrorized processing. -
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MetaGPT
The Multi-Agent Framework
The Multi-Agent Framework: Given one line Requirement, return PRD, Design, Tasks, Repo. Assign different roles to GPTs to form a collaborative software entity for complex tasks. MetaGPT takes a one-line requirement as input and outputs user stories / competitive analysis/requirements/data structures / APIs / documents, etc. Internally, MetaGPT includes product managers/architects/project managers/engineers. It provides the entire process of a software company along with carefully orchestrated... -
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Imagen - Pytorch
Implementation of Imagen, Google's Text-to-Image Neural Network
Implementation of Imagen, Google's Text-to-Image Neural Network that beats DALL-E2, in Pytorch. It is the new SOTA for text-to-image synthesis. Architecturally, it is actually much simpler than DALL-E2. It consists of a cascading DDPM conditioned on text embeddings from a large pre-trained T5 model (attention network). It also contains dynamic clipping for improved classifier-free guidance, noise level conditioning, and a memory-efficient unit design. It appears neither CLIP nor prior network... -
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HDBSCAN
A high performance implementation of HDBSCAN clustering
..., is intuitive and easy to select. HDBSCAN is ideal for exploratory data analysis; it's a fast and robust algorithm that you can trust to return meaningful clusters (if there are any). -
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sktime
A unified framework for machine learning with time series
sktime is a library for time series analysis in Python. It provides a unified interface for multiple time series learning tasks. Currently, this includes time series classification, regression, clustering, annotation, and forecasting. It comes with time series algorithms and scikit-learn compatible tools to build, tune and validate time series models. Our objective is to enhance the interoperability and usability of the time series analysis ecosystem in its entirety. sktime provides a unified... -
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airda
airda(Air Data Agent
airda(Air Data Agent) is a multi-smart body for data analysis, capable of understanding data development and data analysis needs, understanding data, generating data-oriented queries, data visualization, machine learning and other tasks of SQL and Python codes. -
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PromethAI
Open-source framework that gives you AI Agents
PromethAI-Backend is a backend framework for AI-driven automation and knowledge extraction. It is designed to integrate with large language models (LLMs) to provide AI-enhanced workflows, including content generation, summarization, and data analysis. -
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Trame
Weave various components and technologies into a Web App
... under Apache License Version 2.0 which allows users to create open source or commercial applications without any licensing worries. By relying simply on Python and HTML, trame focuses on one's data and associated analysis and visualizations while hiding the complications of web development. -
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PARL
A high-performance distributed training framework
PARL is a scalable reinforcement learning framework built on top of PaddlePaddle. It focuses on modularity and ease of use, supporting distributed training and a variety of RL algorithms. -
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PyRx - Virtual Screening Tool
Virtual Screening software for Computational Drug Discovery
PyRx is a Virtual Screening software for Computational Drug Discovery that can be used to screen libraries of compounds against potential drug targets. PyRx enables Medicinal Chemists to run Virtual Screening from any platform and helps users in every step of this process - from data preparation to job submission and analysis of the results. While it is true that there is no magic button in the drug discovery process, PyRx includes docking wizard with easy-to-use user interface which makes... -
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GMAT
General Mission Analysis Tool
The General Mission Analysis Tool (GMAT) is an open-source tool for space mission design and navigation. GMAT is developed by a team of NASA, private industry, and public and private contributors. The GMAT development team is pleased to announce the release of GMAT version R2025a. For a complete list of new features, compatibility changes, and bug fixes, see the R2025a Release Notes in the Users Guide. -
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DAE Tools Project
Object-oriented equation-based modelling and optimisation software
DAE Tools is a cross-platform equation-based object-oriented modelling, simulation and optimisation software. It is not a modelling language nor a collection of numerical libraries but rather a higher level structure – an architectural design of interdependent software components providing an API for: - Model development/specification - Activities on developed models, such as simulation, optimisation, sensitivity analysis and parameter estimation - Processing of the results... -
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Shennina
Automating Host Exploitation with AI
Shennina is an automated host exploitation framework. The mission of the project is to fully automate the scanning, vulnerability scanning/analysis, and exploitation using Artificial Intelligence. Shennina is integrated with Metasploit and Nmap for performing the attacks, as well as being integrated with an in-house Command-and-Control Server for exfiltrating data from compromised machines automatically. Shennina scans a set of input targets for available network services, uses its AI engine... -
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BashCore
A custom Debian live ISO with security tools, no GUI, only Bash.
BashCore is a custom Debian-based live ISO for security professionals, networking enthusiasts, and students. Minimalist and GUI-free, it relies entirely on Bash. It provides a fresh environment on every boot, ideal for safe experimentation and learning. Lightweight and fast, it works smoothly on VirtualBox and low-resource systems. Includes curated tools for penetration testing, network analysis, and diagnostics. Built with Debian live-build, it’s stable, open-source, and highly... -
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LabRPS
Random phenomena generator
This is an official mirror of LabRPS. Code and release files are primarily hosted on https://github.com/LabRPS/LabRPS and mirrored here LabRPS aims to be a tool for the numerical simulation of random phenomena such as stochastic wind velocity, seismic ground motion, sea surface ... etc. It can be in a wide range of uses around engineering, such as random vibration or vibration fatigue in mechanical engineering, buffeting analysis in bridge engineering.... LabRPS is mainly to assist... -
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Padasip
Python Adaptive Signal Processing
Padasip (Python Adaptive Signal Processing) is a Python library tailored for adaptive filtering and online learning applications, particularly in signal processing and time series forecasting. It includes a variety of adaptive filter algorithms such as LMS, RLS, and their variants, offering real-time adaptation to changing environments. The library is lightweight, well-documented, and ideal for research, prototyping, or teaching purposes. Padasip supports both supervised and unsupervised... -
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Crunch
Insane(ly slow but wicked good) PNG image optimization
Crunch is an image compression tool for lossy PNG image file optimization. Using a combination of selective bit depth, color palette reduction and color type, as well as zopfli DEFLATE compression algorithm encoding that employs the pngquant and zopflipng PNG optimization tools, Crunch is effectively able to optimize and compress images with minimal decrease in image quality. While it may produce file size gains larger than those produced by lossless approaches, the impact on image quality... -
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SLM Lab
Modular Deep Reinforcement Learning framework in PyTorch
SLM Lab is a modular and extensible deep reinforcement learning framework designed for research and practical applications. It provides implementations of various state-of-the-art RL algorithms and emphasizes reproducibility, scalability, and detailed experiment tracking. SLM Lab is structured around a flexible experiment management system, allowing users to define, run, and analyze RL experiments efficiently. -
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StreamAlert
StreamAlert is a serverless, realtime data analysis framework
... or functions. Merge similar alerts and automatically promote new rules if they are not too noisy. Ingested logs and generated alerts can be retroactively searched for compliance and research. Serverless design is cheaper, easier to maintain, and scales to terabytes per day. Deployment is automated, simple, safe and repeatable for any AWS account. Secure by design, least-privilege execution, containerized analysis, and encrypted data storage. -
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DockStream
A Docking Wrapper to Enhance De Novo Molecular Design
DockStream is a docking wrapper providing access to a collection of ligand embedders and docking backends. Docking execution and post hoc analysis can be automated via the benchmarking and analysis workflow. The flexilibity to specifiy a large variety of docking configurations allows tailored protocols for diverse end applications. DockStream can also parallelize docking across CPU cores, increasing throughput. DockStream is integrated with the de novo design platform, REINVENT, allowing one...
