Explore projects
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Rodolphe Lepigre / Iris
BSD 3-Clause "New" or "Revised" LicenseThe Coq development for Iris. [project website] [coqdoc]
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Hugo Herbelin / iris-coq
Creative Commons Attribution 4.0 InternationalThe Coq development for Iris. [project website] [coqdoc]
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cld / ml / tvm
Apache License 2.0Mirror of https://github.com/dmlc/tvm for internal development
Check other branches for active development.
Don't forgot to git submodule init and git submodule update!
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Publicly released Azure Functions traces from https://github.com/Azure/AzurePublicDataset/blob/master/AzureFunctionsDataset2019.md
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ptorrx / PROSA - Formally Proven Schedulability Analysis
BSD 2-Clause "Simplified" LicenseThe main Coq development of the Prosa project: http://prosa.mpi-sws.org
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Alix Trieu / Iris
BSD 3-Clause "New" or "Revised" LicenseThe Coq development for Iris. [project website] [coqdoc]
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Abel Nieto / Iris
BSD 3-Clause "New" or "Revised" LicenseThe Coq development for Iris. [project website] [coqdoc]
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Dmitry Khalanskiy / Iris
Creative Commons Attribution 4.0 InternationalThe Coq development for Iris. [project website] [coqdoc]
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Jules Jacobs / Iris
BSD 3-Clause "New" or "Revised" LicenseThe Coq development for Iris. [project website] [coqdoc]
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The implementation for checking linearizability using hitting families of schedules
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Michael Sammler / iris-coq
Creative Commons Attribution 4.0 InternationalThe Coq development for Iris. [project website] [coqdoc]
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FCS / ocpl-coq
Creative Commons Attribution 4.0 InternationalUpdated -
Abhishek Anand / Iris
Creative Commons Attribution 4.0 InternationalThe Coq development for Iris. [project website] [coqdoc]
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Germán Delbianco / Iris
Creative Commons Attribution 4.0 InternationalThe Coq development for Iris. [project website] [coqdoc]
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Maxime Dénès / iris-coq
Creative Commons Attribution 4.0 InternationalThe Coq development for Iris. [project website] [coqdoc]
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Ayan Majumdar / Bias in VAE
MIT LicenseGenerative Models are being developed currently which can potentially be used for various applications such as data generation for training models. This project aims to analyse a generative model, the Variational Autoencoder and potential bias in it.
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