Search Results for "mimo network coding"
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Showing 29 open source projects for "mimo network coding"
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MiMo Code
Where Models and Agents Co-Evolve
MiMo-Code is a terminal-native AI coding assistant built for real software projects. It can read and edit code, run commands, manage Git, and preserve project knowledge across sessions. The tool includes multiple agent modes, including a build mode for development, a plan mode for read-only analysis, and a compose mode for structured workflows. -
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MiMo-V2-Flash
MiMo-V2-Flash: Efficient Reasoning, Coding, and Agentic Foundation
MiMo-V2-Flash is a large Mixture-of-Experts language model designed to deliver strong reasoning, coding, and agentic-task performance while keeping inference fast and cost-efficient. It uses an MoE setup where a very large total parameter count is available, but only a smaller subset is activated per token, which helps balance capability with runtime efficiency. -
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Kun
AI agent workspace with Code and Write modes built into your apps
Kun is a desktop AI agent workspace focused on a requirement-first coding workflow. Instead of starting with a vague prompt and immediately changing files, it guides users through requirement clarification, design, planning, todos, implementation, and review. The application includes a Code workspace for real repositories and a Write workspace for Markdown writing, editing, previewing, and exporting. It uses DeepSeek, Xiaomi MiMo, and MiniMax as its default model combination while still allowing custom providers. ... -
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OpenAI Codex CLI
Lightweight coding agent that runs in your terminal
...Codex CLI can also handle multimodal inputs like screenshots and diagrams to implement features intelligently. The tool includes built-in sandboxing & security measures, such as network restrictions and directory confinement, to protect your system during code execution. With extensive configuration options, including multiple AI providers and custom guidance files, it fits seamlessly into developer environments. -
Build Agents and Models on One PlatformGemini Enterprise Agent Platform is Google Cloud's comprehensive platform for developers to build, scale, govern, and optimize agents and models. Choose from Google's most advanced models and third-party models like Anthropic's Claude Model Family.
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Graphify
AI coding assistant skill (Claude Code, Codex, OpenCode, OpenClaw)
Graphify is a data visualization and transformation tool designed to convert structured or semi-structured data into graph-based representations, enabling better understanding of relationships and dependencies. It focuses on building visual models such as nodes and edges that represent entities and their connections, making complex datasets easier to interpret. The system likely supports dynamic updates, allowing graphs to evolve as data changes or new inputs are introduced. It is... -
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Edgee
AI gateway with token compression for Claude Code, Codex, and more
Edgee is an edge-native execution platform designed to run AI-driven logic and data processing directly at the network edge, reducing latency and improving responsiveness for modern applications. It enables developers to deploy functions and workflows closer to users, allowing real-time processing without relying heavily on centralized cloud infrastructure. The platform is built to support event-driven architectures, where actions are triggered by incoming requests, user behavior, or... -
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thorough-pytorch
PyTorch Getting Started Tutorial, read online
...The repository provides tutorials and practical exercises that guide learners from fundamental PyTorch concepts to more advanced deep learning techniques. It emphasizes a learning approach that combines theoretical explanations with hands-on coding exercises so that students can build and experiment with neural networks directly. The project encourages collaborative learning and often organizes materials in a step-by-step progression that gradually increases in complexity. Topics include neural network fundamentals, training procedures, model evaluation, and practical deep learning workflows. ... -
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claude-devtools
A desktop app that reconstructs exactly what Claude Code did
claude-devtools is an open-source desktop observability tool designed to provide deep visibility into Claude Code sessions by reconstructing execution activity directly from local session logs. Rather than acting as a wrapper or modifying Claude Code behavior, the application passively reads the logs stored in the user’s environment and rebuilds a structured, searchable timeline of what actually occurred during each session. The tool was created to address the loss of detail in the standard... -
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FlowLens MCP
Open-source MCP server that gives your coding agent
FlowLens MCP Server is an open-source tool designed to give AI-powered coding agents (like Claude Code, Cursor, GitHub Copilot / Codex, and others) full, replayable browser context to dramatically improve debugging, bug reporting, and regression testing for web applications. It works together with a companion browser extension: when a user reproduces a bug or a complicated UI interaction, the extension captures a rich session log, including screen/video recording, network traffic, console logs, DOM events, storage changes, and more, and exports it. ... -
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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Oh My OpenAgent
The best agent harness
Oh My OpenAgent is a large-scale, open-source agent orchestration framework that aims to provide a fully unified and extensible environment for AI-powered software development and automation. It builds on the idea that no single model is sufficient, instead enabling coordinated use of multiple models for reasoning, creativity, speed, and cost efficiency within a single workflow. The system is designed as a comprehensive agent harness where tasks are automatically decomposed, delegated, and... -
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Chrome DevTools MCP
Chrome DevTools for coding agents
chrome-devtools-mcp is an MCP server that connects AI agents to the Chrome DevTools Protocol so they can inspect pages, record traces, read console/network data, and modify the live browser state under user control. It makes a running Chrome instance visible to MCP clients, enabling agents to debug websites end-to-end—launching Chrome, navigating, profiling, and collecting artifacts in a structured way. The repository spells out environment requirements and cautions that exposing a live... -
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nono
Secure, kernel-enforced sandbox CLI and SDKs for AI agents
...Unlike container-based approaches, the tool is intentionally lightweight and can wrap any command-line process without requiring images, VMs, or complex infrastructure. The system emphasizes capability-based security, where processes are granted only the exact filesystem paths and network access they need, and nothing more. -
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PyTorch-Tutorial-2nd
CV, NLP, LLM project applications, and advanced engineering deployment
PyTorch-Tutorial-2nd is an open-source educational repository that provides structured tutorials for learning deep learning with the PyTorch framework. The project serves as a practical companion to a second edition of a PyTorch learning guide and is designed to help learners understand neural network concepts through hands-on coding examples. The repository covers a wide range of topics including tensor operations, neural network construction, model training workflows, and optimization strategies. It also introduces practical machine learning techniques such as convolutional neural networks, recurrent networks, and other architectures commonly used in modern AI applications. ... -
14
serve-sim
The `npx serve` of Apple Simulators
serve-sim is a developer tool for hosting Apple Simulators through a local or network-accessible web interface. It is described as the npx serve equivalent for Apple Simulators, allowing users to preview and control a simulator from a browser. The tool is especially useful for AI coding agents such as Codex, Cursor, and Claude Desktop because they can interact with a simulator through browser-driven workflows. It can run locally, over a LAN, or through a remote Mac with tunneling. ... -
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MiniSom
MiniSom is a minimalistic implementation of the Self Organizing Maps
...Although it has expanded in terms of features, it remains minimalistic by relying only on the numpy library and emphasizing vectorization in coding style. -
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Attention Residuals (AttnRes)
Drop-in replacement for standard residual connections in Transformers
...Attention Residuals introduces a learnable softmax attention mechanism that allows each layer to selectively retrieve and weight useful representations from earlier layers, making depth dynamically adaptive rather than uniformly aggregated. This approach improves gradient stability, preserves meaningful signals throughout the network, and enhances performance in reasoning-heavy tasks such as coding, mathematics, and multi-step problem solving. -
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web-eval-agent MCP Server
An MCP server that autonomously evaluates web applications
web-eval-agent is a Model Context Protocol (MCP) server that spins up a browser-use–capable debugging agent to autonomously run and evaluate web apps straight from your editor. It’s positioned as a “let the coding agent debug itself” companion: the agent launches the app, navigates flows, captures evidence, and iterates on failures without manual copy-pasting of logs. The repository focuses on developer ergonomics, exposing typed MCP tools so clients like Claude Desktop can start sessions,... -
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NodeTool
Visual AI Workflow Builder
NodeTool is an open‑source, visual AI workflow builder that lets you connect nodes for text, images, audio, video, data, and automation—then run them locally or on the cloud. Build multi‑step agents, RAG systems, and creative media pipelines without coding, inspect execution in real time, and deploy anywhere: home server, private VPC, RunPod, or Cloud Run. With a local‑first design, NodeTool keeps models and data under your control while still supporting providers like OpenAI, Anthropic,... -
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HasMCP
Convert API into MCP Server in seconds
HasMCP empowers AI development by seamlessly connecting your existing APIs to Large Language Models. Its Automated OpenAPI Mapping instantly translates API documentation into LLM-usable tools, eliminating manual coding. Security is paramount, with Native MCP Elicitation Auth managing complex authentication flows like OAuth2, ensuring user credentials are never exposed. To enhance efficiency, Context Window Optimization intelligently prunes API responses using JMESPath and Goja (JS) logic,... -
20
edge-TTS-record
Tool that can record speech synthesis
edge-TTS-record is a Windows-based tool that records speech synthesized by the Microsoft Edge browser’s online TTS voices and saves the result as .wav audio files. The idea is simple but effective: since Edge’s online TTS voices (such as “Xiaoxiao” or “Yunyang” for Chinese) are often high-quality, this tool provides a way to “capture” them offline for later use. Users can type or paste text, preview the speech, and then trigger the recorder; the system automatically captures the audio output... -
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Next Generation Programming
Compose Software Without Writing Any Programing Code
"Next Generation Programming - Programming Without Coding Software" is a drag-drop wizard for creating simple or complex applications without writing any programming language code The Software is coded/designed with "Java Programming Language" for novice/expert programmers; Programmers can write softwares with visual tools : drag-drop components;visual editors... Programmers can use the software to compose of simple/complex applications : Database programs, circuit design, generate... -
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Machine Learning & Deep Learning
machine learning and deep learning tutorials, articles
Machine Learning & Deep Learning Tutorials is an open-source repository that provides practical tutorials demonstrating how to implement machine learning and deep learning models using popular frameworks such as TensorFlow and PyTorch. The project focuses on helping learners understand machine learning through hands-on coding examples rather than purely theoretical explanations. Each tutorial walks through the process of building and training models for tasks such as image classification, neural network training, and computer vision applications. The repository also includes explanations of how different algorithms function internally, helping readers connect theoretical knowledge with implementation details. ... -
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Teachable Machine
Explore how machine learning works, live in the browser
Teachable Machine is the open-source implementation of an experimental machine learning tool created by Google Creative Lab that allows users to train simple machine learning models directly in a web browser. The project demonstrates how neural networks can be trained interactively using images captured from a webcam or other inputs without requiring programming knowledge. Users can provide example images for different categories, and the system trains a model that learns to classify those... -
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Tabnine
Vim client for TabNine
Tabnine is an AI-powered code completion extension trusted by millions of developers around the world. Whether you’re just getting started as a developer or if you’ve been doing it for decades, Tabnine will help you code twice as fast with half the keystrokes – all in your favorite IDE. Whether you call it IntelliSense, intelliCode, autocomplete, AI-assisted code completion, AI-powered code completion, AI copilot, AI code snippets, code suggestion, code prediction, code hinting, or... -
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DeepTraffic
DeepTraffic is a deep reinforcement learning competition
...The system presents a simulated multi-lane highway where an AI-controlled vehicle must navigate traffic while maximizing speed and avoiding collisions. Participants design neural network policies that determine the vehicle’s actions, such as accelerating, decelerating, changing lanes, or maintaining speed. The project was created as part of an educational competition associated with MIT’s deep learning courses, encouraging students and researchers to experiment with reinforcement learning techniques. The environment provides a coding interface where users can design neural network architectures and tune hyperparameters while observing their agent’s performance in a visual simulation.
