Search Results for "g-code"
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Showing 58 open source projects for "g-code"
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AutoResearchClaw
Autonomous research from idea to paper. Chat an Idea. Get a Paper 🦞
...Built in Python, it orchestrates a multi-stage research pipeline that gathers literature, formulates hypotheses, runs experiments, analyzes results, and writes the final paper. The system retrieves real academic references from sources such as arXiv and Semantic Scholar to ensure credible citations. It can automatically generate code for experiments, run them in a sandbox environment, and analyze the results with statistical methods. The platform also uses multi-agent debate and automated peer review processes to refine research findings and improve paper quality. By combining literature discovery, experimentation, and writing automation, AutoResearchClaw aims to turn research ideas into conference-ready papers with minimal human intervention. -
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nanoGPT
The simplest, fastest repository for training/finetuning models
NanoGPT is a minimalistic yet powerful reimplementation of GPT-style transformers created by Andrej Karpathy for educational and research use. It distills the GPT architecture into a few hundred lines of Python code, making it far easier to understand than large, production-scale implementations. The repo is organized with a training pipeline (dataset preprocessing, model definition, optimizer, training loop) and inference script so you can train a small GPT on text datasets like Shakespeare or custom corpora. It emphasizes readability and clarity: the training loop is cleanly written, and the code avoids heavy abstractions, letting students follow the architecture step by step. ... -
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Containerization (Apple)
Containerization is a Swift package for running Linux containers
...Developers get a blueprint for taking standard container images and running them in a way that respects platform conventions, tooling, and policies. The emphasis is on clarity and standards alignment rather than building a production-grade engine, which makes the code ideal for learning and experimentation. -
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Open Science
Open Science is an open-source, local-first, model-agnostic research
...Users can inspect tool activity, approve sensitive actions, branch earlier conversations, and compare alternative research paths without losing prior work. Immutable artifact versions and detailed provenance connect results to code, inputs, execution history, environment evidence, conversation context, and review findings. -
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OpenScience
The open-source AI workbench for scientific research
OpenScience is an open-source AI workbench for scientific research. It lets users give an agent a research goal, then have it read literature, form hypotheses, write and run code, run experiments, analyze results, and write up findings. The workspace runs in the browser and includes a file tree, editor, terminal, session history, and scientific rendering for molecules, structures, genomes, and plots. It supports frontier, open-weight, and local models through bring-your-own-key provider configuration. The project includes research agents, domain specialists, critique agents, literature-review agents, and more than 290 scientific skills. ... -
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Qualify
Claude code to help you do lead research and qualification
...Built with simplicity and extensibility in mind, the project includes REST APIs, database models, and a user interface that can be extended or embedded into existing internal systems. Because it prioritizes lean data structures and predictable code paths, developers can customize pipelines, fields, and behaviors to align with their unique business logic. -
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AI Researcher
An autonomous AI researcher
...It orchestrates agents that can generate research questions, perform literature reviews, execute experiments, analyze results, and synthesize findings into structured outputs like reports or code. Each agent operates with clear roles — such as researcher, analyst, and summarizer — and they communicate through a task-management interface that ensures progress tracking and iterative refinement. The system emphasizes modularity, so teams can swap in new reasoning modules, data retrieval strategies, or domain knowledge bases depending on the research topic. ... -
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ThingPulse ESP8266 Weather Station
ESP8266 Weather Station library supporting OpenWeatherMap
...The simple class uses the header date and time to set the clock. NTP-based time class written by Fabrice Weinberg. We fixed many bugs and improved performance and changed the API a little bit. Either compare your code to the updated WeatherStationDemo or read through the upgrade guide. -
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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. Each growth model follows an observe-act-review loop and keeps persistent memory of evidence, actions, results, and recommended next steps. ... -
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ClooWrapperVBA
COM-wrapper of Cloo to execute OpenCL code from Excel.
The wrapper allows to execute OpenCL code on CPU and GPU devices from VBA. Sources are available under https://github.com/Excel-lent/ClooWrapperVBA -
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KingJamesPureBibleSearch
GUI Application to Search and Count the Pure King James Bible
...For more info and downloads, see http://www.purebiblesearch.com/ For details on the King James Code, see http://visitbethelchurch.com/ -
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Bloom Filter Analysis UCSB130A
Supporting Code for Bloom Filter Analysis UCSB CMPSC 130A F22
The full code set that corresponds to "Bloom Filters: A Look into its Design and an Analysis of its Performance", written by David Jr Sim. Instructions on how to use it are included in this project. This paper is in correlation with the University of California, Santa Barbara, Computer Science Undergraduate. -
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Brain Tokyo Workshop
Experiments and code from Google Brain’s Tokyo research workshop
The Brain Tokyo Workshop repository hosts a collection of research materials and experimental code developed by the Google Brain team based in Tokyo. It showcases a variety of cutting-edge projects in artificial intelligence, particularly in the areas of neuroevolution, reinforcement learning, and model interpretability. Each project explores innovative approaches to learning, prediction, and creativity in neural networks, often through unconventional or biologically inspired methods. ... -
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Catalyst
Accelerated deep learning R&D
Catalyst is a PyTorch framework for accelerated Deep Learning research and development. It allows you to write compact but full-featured Deep Learning pipelines with just a few lines of code. With Catalyst you get a full set of features including a training loop with metrics, model checkpointing and more, all without the boilerplate. Catalyst is focused on reproducibility, rapid experimentation, and codebase reuse so you can break the cycle of writing another regular train loop and make something totally new. Catalyst is compatible with Python 3.6+. ... -
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Key Store
Scriptural Keys Restoration - decoded universally symbolic language
The Key Store is a directory where users can find the symbolic meaning to a word as defined in Holy Scripture. These are often referred to as the keys of the Kingdom of Heaven. Much like a secret code, the directory exposes a universal dialect, all but nearly lost throughout the Dark Ages of time. Yet, fragments of this language remained until today such as, Father = Time and Mother = Nature. The database is expandable to grow as more entries and the sources are uncovered. -
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PureGEM
A new GUI library for Atari ST/TT/Falcon computers
...This is a new library, so expect code to change. I will be working on this for the next 1-2 years. cheers Derek -
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MolMarker
Java software to evaluate the results obtained by molecular markers
Journal article to cite: Jahnke, G.; Smidla, J.; Poczai, P. MolMarker: A Simple Tool for DNA Fingerprinting Studies and Polymorphic Information Content Calculation. Diversity 2022, 14, 497. https://doi.org/10.3390/d14060497 Leave a review, please! Your opinion matters! :-) MolMarker is user-friendly software to help evaluate the research results obtained by molecular markers. -
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VXUG-Papers
Research code & papers from members of vx-underground
VXUG-Papers is an archive of security research papers, proof-of-concept code, and technical experiments contributed by members of the vx-underground community. Its contents focus heavily on malware research, operating system internals, persistence, process behavior, propagation, and offensive-security techniques. The repository mixes written papers with source files, demonstrations, and project folders. Topics span Windows, Linux, Android, virtualization, credential research, loaders, and other low-level subjects. ... -
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covid19model
Code for modelling estimated deaths and cases for COVID19
...Peer-reviewed version is to be out soon. All other code is still the same for previous releases. The code should be run in full mode to obtain credible results. Not running a full run to estimate anything is not recommended and discouraged. Only a full run should be used to get results. -
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Lucid
A collection of infrastructure and tools for research
Lucid is a collection of infrastructure and tools for research in neural network interpretability. Lucid is research code, not production code. We provide no guarantee it will work for your use case. Lucid is maintained by volunteers who are unable to provide significant technical support. Start visualizing neural networks with no setup. The following notebooks run right from your browser, thanks to Collaboratory. It's a Jupyter notebook environment that requires no setup to use and runs entirely in the cloud. ... -
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hubs-research-acm-chi-2021
Supplemental code and dataset for the ACM CHI 2021 paper
Supplemental code and dataset for the ACM CHI 2021 paper on "Proxemics and Social Interactions in an Instrumented Virtual Reality Workshop". In this research paper we instrumented Mozilla Hubs Cloud to record where participants where during the event. From there, we measured proxemic and plotted the activity along with some semi-structured interviews. -
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DeepMind Lab
A customizable 3D platform for agent-based AI research
DeepMind Lab is a 3D learning environment based on id Software's Quake III Arena via ioquake3 and other open source software. DeepMind Lab provides a suite of challenging 3D navigation and puzzle-solving tasks for learning agents. Its primary purpose is to act as a testbed for research in artificial intelligence, especially deep reinforcement learning. If you use DeepMind Lab in your research and would like to cite the DeepMind Lab environment, we suggest you cite the DeepMind Lab paper. To... -
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wav2letter++
Facebook AI research's automatic speech recognition toolkit
...All results reproduction must use Flashlight <= 0.3.2 for exact reproducibility. At least one of LZMA, BZip2, or Z is required for LM compression with KenLM. It is highly recommended to build KenLM with position-independent code (-fPIC) enabled, to enable python compatibility. After installing, run export KENLM_ROOT_DIR=... so that wav2letter++ can find it. This is needed because KenLM doesn't support a make install step.wav2letter++ expects audio and transcription data to be prepared in a specific format so that they can be read from the pipelines. Each dataset (test/valid/train) needs to be in a separate file with one sample per line. ... -
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...Installation Videos! Part 1: http://youtu.be/rnv2VLcG-eI Part 2: http://youtu.be/eFudbMWHNlQ Special thanks to Wells Oliver for the code for downloading Retrosheet files. And the Chadwick project for its Retrosheet tools. https://sourceforge.net/projects/chadwick/?source=recommended
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Data Science at the Command Line
Data science at the command line
Command Line by Jeroen Janssens, published by O’Reilly Media in October 2021. Obtain, scrub, explore, and model data with Unix Power Tools. This repository contains the full text, data, and scripts used in the second edition of the book Data Science at the Command Line by Jeroen Janssens. This thoroughly revised guide demonstrates how the flexibility of the command line can help you become a more efficient and productive data scientist. You’ll learn how to combine small yet powerful...
