Search Results for "lab"
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Showing 104 open source projects for "lab"
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Habitat-Lab
A modular high-level library to train embodied AI agents
Habitat-Lab is a modular high-level library for end-to-end development in embodied AI. It is designed to train agents to perform a wide variety of embodied AI tasks in indoor environments, as well as develop agents that can interact with humans in performing these tasks. Allowing users to train agents in a wide variety of single and multi-agent tasks (e.g. navigation, rearrangement, instruction following, question answering, human following), as well as define novel tasks. -
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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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Growth Lab
An end-to-end growth tool that understands the product
Growth Lab is an open-source agentic growth workspace that connects product understanding, market research, execution, measurement, and iteration. It uses Codex or Claude Code as the runtime and treats natural-language conversations as the control surface. Collectors gather product, market, content, and channel evidence, while executor skills help create, publish, review, and coordinate growth work. -
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Harvey LAB
A benchmark built to evaluate and improve agent capabilities
Harvey LAB is an open-source benchmark for evaluating how effectively AI agents perform realistic legal work. It combines a dataset of legal assignments with an execution harness that runs agents against those tasks. Each benchmark task includes instructions, working documents, and rubrics that define successful completion. The environment is designed to test practical legal workflows rather than isolated question-answering ability. -
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NVIDIA Isaac Lab
Unified framework for robot learning built on NVIDIA Isaac Sim
Isaac Lab is an open-source modular robotics learning framework built atop Isaac Sim. It simplifies research workflows across reinforcement learning, imitation learning, and motion planning by offering robust, GPU-accelerated simulation with realistic sensor and physics fidelity—ideal for sim-to-real robot training. Compatible and optimized for use with Isaac Sim versions (e.g., Sim 5.0 and 4.5). -
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Advanced Solutions Lab
This repos contains notebooks for the Advanced Solutions Lab
This repository contains Jupyter notebooks meant to be run on Vertex AI. This is maintained by Google Cloud’s Advanced Solutions Lab (ASL) team. Vertex AI is the next-generation AI Platform on the Google Cloud Platform. The material covered in this repo will take a software engineer with no exposure to machine learning to an advanced level. -
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Mobile Verification Toolkit
Helps with conducting forensics of mobile devices
Mobile Verification Toolkit (MVT) is a collection of utilities to simplify and automate the process of gathering forensic traces helpful to identify a potential compromise of Android and iOS devices. It has been developed and released by the Amnesty International Security Lab in July 2021 in the context of the Pegasus project along with a technical forensic methodology and forensic evidence. MVT is a forensic research tool intended for technologists and investigators. Using it requires understanding the basics of forensic analysis and using command-line tools. This is not intended for end-user self-assessment. ... -
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AutoKeras
AutoML library for deep learning
AutoKeras: An AutoML system based on Keras. It is developed by DATA Lab at Texas A&M University. The goal of AutoKeras is to make machine learning accessible to everyone. AutoKeras only support Python 3. If you followed previous steps to use virtualenv to install tensorflow, you can just activate the virtualenv. Currently, AutoKeras is only compatible with Python >= 3.7 and TensorFlow >= 2.8.0. AutoKeras supports several tasks with extremely simple interface. -
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STORM
An LLM-powered knowledge curation system that researches topics
STORM is an open-source virtual assistant framework developed by Stanford's OVAL lab. It is designed for creating natural language interfaces and assistants that can interact with APIs, databases, and services in a modular way. -
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JupyterLab LaTeX
JupyterLab extension for live editing of LaTeX documents
...To use, right-click on an open .tex document within JupyterLab, and select Show LaTeX Preview. This extension includes both a notebook server extension (which interfaces with the LaTeX compiler) and a lab extension (which provides the UI for the LaTeX preview). The Python package named jupyterlab_latex provides both of them as a prebuilt extension. -
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Splunk Attack Range
A tool that allows you to create vulnerable environments
The Splunk Attack Range is an open-source project maintained by the Splunk Threat Research Team. It builds instrumented cloud (AWS, Azure) and local environments (Virtualbox), simulates attacks, and forwards the data into a Splunk instance. This environment can then be used to develop and test the effectiveness of detections. -
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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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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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Hackingtool
ALL IN ONE Hacking Tool For Hackers
...A menu interface offering categories: reconnaissance, payload creation, wireless attacks, reverse engineering, exploit frameworks, etc. Users can pick which tool to run. It is intended more for “ethical / lab / educational” hacking contexts rather than production or stealth scenarios. It depends a lot on external tools, grants, and root privileges in many cases. -
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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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Qiskit
Qiskit is an open-source SDK for working with quantum computers
...When you are looking to start Qiskit, you have two options. You can start Qiskit locally, which is much more secure and private, or you get started with Jupyter Notebooks hosted in IBM Quantum Lab. Qiskit includes a comprehensive set of quantum gates and a variety of pre-built circuits so users at all levels can use Qiskit for research and application development. The transpiler translates Qiskit code into an optimized circuit using a backend’s native gate set, allowing users to program for any quantum processor or processor architecture with minimal inputs. ... -
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FISSURE
The RF and reverse engineering framework for everyone
...The platform supports workflows related to signal discovery, demodulation, packet inspection, fuzzing, and attack simulation, making it useful for both defensive research and controlled lab testing. Its architecture is oriented toward extensibility, so users can integrate additional hardware, signal-processing components, and protocol-specific modules depending on their needs. -
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Nerfstudio
A collaboration friendly studio for NeRFs
...This is a contributor-friendly repo with the goal of building a community where users can more easily build upon each other’s contributions. Nerfstudio initially launched as an opensource project by Berkeley students in KAIR lab at Berkeley AI Research (BAIR) in October 2022 as a part of a research project (paper). It is currently developed by Berkeley students and community contributors. We are committed to providing learning resources to help you understand the basics of (if you’re just getting started), and keep up-to-date with (if you’re a seasoned veteran) all things NeRF. -
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AtomAI
Deep and Machine Learning for Microscopy
AtomAI is a Pytorch-based package for deep and machine-learning analysis of microscopy data that doesn't require any advanced knowledge of Python or machine learning. The intended audience is domain scientists with a basic understanding of how to use NumPy and Matplotlib. It was developed by Maxim Ziatdinov at Oak Ridge National Lab. The purpose of the AtomAI is to provide an environment that bridges the instrument-specific libraries and general physical analysis by enabling the seamless deployment of machine learning algorithms including deep convolutional neural networks, invariant variational autoencoders, and decomposition/unmixing techniques for image and hyperspectral data analysis. ... -
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Jupytext
Jupyter Notebooks as Markdown Documents, Julia, Python or R scripts
...Text notebooks with a .py or .md extension are well suited for version control. They can be edited or authored conveniently in an IDE. You can open and run them as notebooks in Jupyter Lab with a right click. However, the notebook outputs are lost when the notebook is closed, as only the notebook inputs are saved in text notebooks. -
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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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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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A.I.G (AI-Infra-Guard)
Full-stack AI Red Teaming platform
AI-Infra-Guard is a powerful open-source security platform from Tencent’s Zhuque Lab designed to assess the safety and resilience of AI infrastructures, codebases, and components through automated scanning and evaluation tools. It brings together AI infrastructure vulnerability scanning, MCP server risk analysis, and jailbreak evaluation into a unified workflow so that enterprises and individuals can identify critical security issues without relying on external services. -
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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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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. ...
