Search Results for "v-lab" - Page 5
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Showing 1495 open source projects for "v-lab"
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ManiSkill
SAPIEN Manipulation Skill Framework
ManiSkill is a benchmark platform for training and evaluating reinforcement learning agents on dexterous manipulation tasks using physics-based simulations. Developed by Hao Su Lab, it focuses on robotic manipulation with diverse, high-quality 3D tasks designed to challenge perception, control, and planning in robotics. ManiSkill provides both low-level control and visual observation spaces for realistic learning scenarios. -
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BindsNET
Simulation of spiking neural networks (SNNs) using PyTorch
...This package is used as part of ongoing research on applying SNNs to machine learning (ML) and reinforcement learning (RL) problems in the Biologically Inspired Neural & Dynamical Systems (BINDS) lab. -
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Tock OS
A secure embedded operating system for microcontrollers
Tock is a secure, embedded operating system designed for microcontrollers and low-power hardware platforms. Written in Rust, it uses a novel kernel architecture where the OS runs a minimal trusted core and all userland code, including device drivers, is sandboxed and isolated. Tock is ideal for IoT devices, wearables, and embedded research projects where reliability and safety are critical. Its capability-based security model and preemptive multitasking allow developers to safely run... -
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Privilege-Escalation
This cheasheet is aimed at the CTF Players and Beginners
...Topics include sudo permissions, SUID binaries, kernel weaknesses, scheduled jobs, Linux capabilities, writable files, containers, databases, and network services. Individual guides connect these concepts to vulnerable lab machines and CTF examples. This structure helps learners recognize recurring misconfigurations and understand why they create security risk. The collection is primarily focused on Linux-oriented privilege escalation and educational security practice. -
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Pedalboard
A Python library for audio
...It supports the most popular audio file formats and a number of common audio effects out of the box and also allows the use of VST3® and Audio Unit formats for loading third-party software instruments and effects. pedalboard was built by Spotify’s Audio Intelligence Lab to enable using studio-quality audio effects from within Python and TensorFlow. Internally at Spotify, pedalboard is used for data augmentation to improve machine learning models and to help power features like Spotify’s AI DJ and AI Voice Translation. pedalboard also helps in the process of content creation, making it possible to add effects to audio without using a Digital Audio Workstation. -
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WIREDOOR
Self hosted ingress-as-a-service platform
...The platform is designed for users who want cloud-like ingress management while keeping the infrastructure under their own control. Wiredoor can expose HTTP and TCP services and is positioned as a secure way to publish internal tools, dashboards, home lab services, or business applications. Its ecosystem includes a CLI, documentation, Helm charts, Docker setup, and related deployment resources. The project is best suited for teams or advanced self-hosters who want structured service exposure through a managed tunnel platform. -
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CoreFreq
CPU monitoring and tuning software designed for the 64-bit processors
...It is designed to retrieve processor data with a high degree of precision and expose details that are often hidden from simpler monitoring utilities. The project supports a wide range of processor families, including Intel, AMD, Arm A64, RISC-V RV64, and PowerPC64 little-endian systems. It provides BIOS-like visibility into CPU behavior, including frequencies, ratios, topology, temperatures, power, and performance counters. CoreFreq is useful for Linux users who need deep hardware insight for tuning, benchmarking, diagnostics, or overclocking research. Its main value is giving advanced users detailed processor telemetry through a specialized driver, daemon, and command-line interface. -
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OpenHealth
AI health assistant for private, local data-driven insights mgmt
OpenHealth is an AI-powered health assistant designed to help individuals take control of their personal health data and better understand their overall well-being. It works by aggregating various types of health information, such as clinical records, wearable device data, and self-reported inputs, into a unified and structured format. OpenHealth then uses large language models to enable contextual conversations, allowing users to interact with their own health data in a more intuitive and... -
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Sygil WebUI
Stable Diffusion web UI
...The UI exposes core generation controls like resolution, CFG guidance, sampling steps, samplers, seeds, and batch generation so users can reproduce results and refine outputs systematically. It also supports jumping between workflows, such as sending an output directly into Image2Image for variations or into an “Image Lab” style area for enhancement and upscaling. Post-processing and enhancement are a major emphasis: the interface can route images through different upscalers and face-enhancement tools, helping users turn raw generations into cleaner, higher-resolution results. -
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DeepLabCut
Implementation of DeepLabCut
...The package is open source, fast, robust, and can be used to compute 3D pose estimates or for multi-animals. Please see the original paper and the latest work below! This package is collaboratively developed by the Mathis Group & Mathis Lab at EPFL (releases prior to 2.1.9 were developed at Harvard University). The code is freely available and easy to install in a few clicks with Anaconda (and pypi). DeepLabCut is an open-source Python package for animal pose estimation. -
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JEPA
PyTorch code and models for V-JEPA self-supervised learning from video
JEPA (Joint-Embedding Predictive Architecture) captures the idea of predicting missing high-level representations rather than reconstructing pixels, aiming for robust, scalable self-supervised learning. A context encoder ingests visible regions and predicts target embeddings for masked regions produced by a separate target encoder, avoiding low-level reconstruction losses that can overfit to texture. This makes learning focus on semantics and structure, yielding features that transfer well... -
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Tongyi DeepResearch
Tongyi Deep Research, the Leading Open-source Deep Research Agent
DeepResearch (Tongyi DeepResearch) is an open-source “deep research agent” developed by Alibaba’s Tongyi Lab designed for long-horizon, information-seeking tasks. It’s built to act like a research agent: synthesizing, reasoning, retrieving information via the web and documents, and backing its outputs with evidence. The model is about 30.5 billion parameters in size, though at any given token only ~3.3B parameters are active. It uses a mix of synthetic data generation, fine-tuning and reinforcement learning; supports benchmarks like web search, document understanding, question answering, “agentic” tasks; provides inference tools, evaluation scripts, and “web agent” style interfaces. ... -
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BSC
Bluespec Compiler (BSC)
...The ecosystem includes standard libraries, FIFOs, interfaces, and utilities that encourage reuse and clean separation of datapaths and control. By raising the abstraction for hardware architecture while preserving efficient output, BSC helps teams explore complex designs—such as RISC-V cores or accelerators—more productively. -
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ProtoMotions
ProtoMotions is a GPU-accelerated simulation and learning framework
...Large motion datasets such as AMASS and BONES can be divided across multiple GPUs for scalable policy training. A built-in PyRoki workflow retargets human motion data to different robot bodies with a single command. Policies can be tested across Isaac Gym, Isaac Lab, Newton, Genesis, MuJoCo, and high-fidelity Isaac Sim environments. Its deployment pipeline exports ONNX policies with observation processing included, simplifying transfers from simulation to real Unitree G1 hardware. The framework also supports procedural scene generation and motion authoring from Kimodo text-to-motion outputs. -
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Zvec
A lightweight, lightning-fast, in-process vector database
Zvec is an open-source, lightweight, in-process vector database designed to embed directly into applications and serve fast similarity search workloads without the overhead of a separate server process. Developed by Alibaba’s Tongyi Lab, it positions itself as the “SQLite of vector databases” by being easy to integrate, minimal in dependencies, and capable of handling high throughput with low latency on edge devices or small systems. Zvec excels at approximate nearest neighbor search and retrieval tasks that power features like semantic search, recommendation systems, and retrieval-augmented generation (RAG) setups. ... -
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Orion
A machine learning library for detecting anomalies in signals
Orion is a machine-learning library built for unsupervised time series anomaly detection. Such signals are generated by a wide variety of systems, few examples include telemetry data generated by satellites, signals from wind turbines, and even stock market price tickers. We built this to provide one place where users can find the latest and greatest in machine learning and deep learning world including our own innovations. Abstract away from the users the nitty-gritty about preprocessing,... -
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Electron Packager
Customize and package your Electron app with OS-specific bundles
...A zipped, minimal Electron application is approximately the same size as the zipped prebuilt binary for a given target platform, target arch, and Electron version (files named electron-v${version}-${platform}-${arch}.zip). Building an Electron app for the Windows target platform requires editing the Electron.exe file. Currently, Electron Packager uses node-rcedit to accomplish this. -
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Algebraic graphs
Algebraic graphs
...See this Haskell Symposium paper and the corresponding talk for the motivation behind the library, the underlying theory and implementation details. We can give semantics to the constructors in terms of the pair (V, E) of graph vertices and edges. Alga can handle graphs comprising millions of vertices and billions of edges in a matter of seconds, which is fast enough for many applications. We believe there is a lot of potential for improving the performance of the library, and this is one of our top priorities. If you come across a performance issue when using the library, please let us know. -
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tt-metal
TT-NN operator library, and TT-Metalium low level kernel programming
...Instead of following a traditional GPU model centered on massive thread parallelism, the platform is built around a grid of specialized compute nodes called Tensix cores, each with local SRAM, dedicated compute units, and multiple RISC-V control processors. The SDK provides the abstractions and APIs needed to manage data movement, compute kernels, memory coordination, and execution flow across this architecture. -
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bash-completion
Programmable completion functions for bash
...If you find that a given function is producing errors or does not work as it should under certain circumstances when you attempt completion, try running set -x or set -v prior to attempting the completion again. -
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Halide
A language for fast, portable data-parallel computation
Halide is a programming language for fast, portable data-parallel computation. It was designed to make writing high-performance image and array processing code much easier on modern machines. It works on all major operating systems and with several CPU architectures (X86, ARM, MIPS, Hexagon, PowerPC) and GPU Compute APIs (CUDA, OpenCL, OpenGL, among others). It isn't a standalone programming language however; rather it is embedded in C++ which means that you write C++ code, building an... -
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GR00T Whole-Body Control (WBC)
Welcome to GR00T Whole-Body Control (WBC)
...Released Unitree G1 checkpoints support motion references, whole-body teleoperation, planning, and vision-language-action workflows. A C++ and TensorRT inference stack provides real-hardware deployment, while PyTorch checkpoints support Isaac Lab evaluation and continued training. The repository also includes VR teleoperation, data collection, kinematic planning, and low-latency control configurations. MotionBricks adds real-time latent motion generation for interactive animation and robotics applications. -
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Little Book of Linear Algebra
A concise, beginner-friendly introduction to the core ideas of linear
...The material is organized into chapters covering vectors, matrices, linear systems, vector spaces, eigenvalues/eigenvectors, and other central topics, each with worked examples and explanations. There is also a companion “LAB” section for hands-on exploration (e.g. using Python/NumPy) to help cement the connections between algebraic formulas and computational behavior. The exposition aims to sit between a pop-math summary and a heavy textbook: definitions and key theorems are stated cleanly, while proofs are sometimes omitted or sketched to keep the flow digestible. ... -
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aws-devops-zero-to-hero
AWS zero to hero repo for devops engineers to learn AWS in 30 Days
...The README is structured as a day-by-day syllabus, starting with “Day 1: Introduction to AWS” and moving through IAM, EC2, VPC networking, security, DNS (Route 53), storage (S3), and many other core services. Each day mixes explanation with at least one concrete project or lab, such as deploying applications on EC2, designing secure VPCs, setting up CI/CD pipelines, or configuring CloudWatch monitoring. Later in the curriculum, you move into topics like CloudFormation, CodeCommit/CodePipeline/CodeBuild/CodeDeploy, Terraform on AWS, CloudTrail and Config for compliance, Elastic Load Balancing, and cloud migration strategies. ... -
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oneDNN
oneAPI Deep Neural Network Library (oneDNN)
...The library is optimized for Intel(R) Architecture Processors, Intel Processor Graphics and Xe Architecture graphics. oneDNN has experimental support for the following architectures: Arm* 64-bit Architecture (AArch64), NVIDIA* GPU, OpenPOWER* Power ISA (PPC64), IBMz* (s390x), and RISC-V. oneDNN is intended for deep learning applications and framework developers interested in improving application performance on Intel CPUs and GPUs. Deep learning practitioners should use one of the applications enabled with oneDNN.
