Showing 4 open source projects for "code new roman"

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    AI Researcher

    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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  • 2
    Catalyst

    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+. ...
    Downloads: 2 This Week
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  • 3
    hubs-research-acm-chi-2021

    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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  • 4

    ArgSemSAT

    Solving argumentation problems in Dung's AFs

    Deprecated hosting for this project. The new hosting is at https://github.com/federicocerutti/ArgSemSAT In particular, the source code for the publication: Federico Cerutti, Massimiliano Giacomin, Mauro Vallati, How we designed winning algorithms for abstract argumentation and which insight we attained, Artificial Intelligence, Volume 276, 2019, Pages 1-40, ISSN 0004-3702, https://doi.org/10.1016/j.artint.2019.08.001.
    Downloads: 0 This Week
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