Explore projects
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LASER(https://www.irit.fr/lase) is a research project funded by the French National Research Agency (ANR) which main objective is to investigate how to better understand and support students’ self-regulated learning (SRL) strategies in BL.
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sepia-pub / Open Science / Expe replay feedback
GNU General Public License v3.0 or laterPublished in FGCS in 2024:
Maël Madon, Georges da Costa, Jean-Marc Pierson. Replay with Feedback: How does the performance of HPC system impact user submission behavior?. Future Generation Computer Systems, inPress, ⟨10.1016/j.future.2024.01.024⟩. ⟨hal-04432711⟩
Artefact: https://gitlab.irit.fr/sepia-pub/open-science/expe-replay-feedback/-/tree/fgcs-2024
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Published in Euro-Par 2022:
Maël Madon, Georges da Costa, Jean-Marc Pierson. Characterization of Different User Behaviors for Demand Response in Data Centers. 28th International Conference on Parallel and Distributed Computing : Parallel Processing (Euro-Par 2022), Aug 2022, Glasgow, United Kingdom. pp.53-68, ⟨10.1007/978-3-031-12597-3_4⟩. ⟨hal-03768237⟩
Artefact : https://gitlab.irit.fr/sepia-pub/open-science/demand-response-user/-/tree/europar2022
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sepia-pub / LightOM2M
OtherLightOM2M WILL BE AVAILABLE ON NOVEMBER 2022.
This projet is an opensource to deploy oneM2M architecture on very constrained devices. It implements a common service entity (CSE) at the gateway level. Typical usage could be on microcontroller like ESP8266.
This project has been partially founded by Toulouse Tech Transfert in a valorisation process and developed inside laboratories of CNRS. It is now managed mainly at IRIT.
Contact: thierry.monteil@irit.fr
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Code for the paper:
Charlotte Roze, Chloé Braud, Philippe Muller. Which aspects of discourse relations are hard to learn? Primitive decomposition for discourse relation classification. Annual SIGdial Meeting on Discourse and Dialogue, Sep 2019.
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poquet / dz-ci-prototype
MIT LicenseUpdated -
MAMBO / psf_projects / eigenpsf-extractor
GNU General Public License v3.0 onlyThis Fiji plugin allows you to extract PSFs from 2D and 3D images and finely estimate eigenpsf : a basis allowing you to represent PSFs compactly.
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