Yannis Karmim

Yannis Karmim

PhD student in Dynamic Graphs for Graph Neural Networks and Recommendation

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A list of all the posts and pages found on the site. For you robots out there is an XML version available for digesting as well.

Pages

Posts

Cours graphes

less than 1 minute read

Published:

Liste de liens de cours et playlist pour l’apprentissage sur des graphes

Expressivité des GNNs

23 minute read

Published:

Note de blog sur l’expressivité des modèles GNNs statiques et dynamiques

Scrapping Paper digest Highlights

1 minute read

Published:

Quick tool to scrape the latest machine learning conferences and perform keyword searches. The code returns a display of article titles and a short text describing the main contributions of the article.

portfolio

publications

(QUIET DRONES) Deeplomatics: A deep-learning based multimodal approach for aerial drone detection and localization

Published in QUIET DRONES Second International e-Symposium on UAV/UAS Noise, 2022

I participated in the DEEPLOMATICS project as a research engineer at the CEDRIC laboratory of CNAM from October 2020 to September 2021. My task was to design a drone detection algorithm on images from very few amount of labeled data.

Recommended citation: Éric Bavu, Hadrien Pujol, Alexandre Garcia, Christophe Langrenne, Sébastien Hengy, et al.. Deeplomatics: A deep-learning based multimodal approach for aerial drone detection and localization. QUIET DRONES Second International e-Symposium on UAV/UAS Noise, INCE/Europe; CidB, Jun 2022, Paris, France. ⟨hal-03707115⟩ https://hal.archives-ouvertes.fr/hal-03707115/

(TMLR) ITEM: Improving Training and Evaluation of Message-Passing based GNNs for top-k recommendation

Published in Transaction on Machine Learning Research, 2024

First paper of the PhD. I worked on the improvement of Message-Passing based GNN for the task of top-k recommandation. Our contribution is to use a loss that better align the item ranking of a user

Recommended citation: Karmim, Y., Ramzi, E., Fournier-S’niehotta, R., & Thome, N. (2024). ITEM: Improving Training and Evaluation of Message-Passing based GNNs for top-k recommendation. Transaction in Machine Learning Research (TMLR). https://arxiv.org/abs/2407.07912v1 https://arxiv.org/abs/2407.07912

(ECML2024 MLG Worshop) Temporal receptive field in dynamic graph learning: A comprehensive analysis

Published in European machine learning and data mining conference (ECML). 2024, 2024

We analysed the temporal receptive field on multiple dynamic graphs models as well as many real-world discrete-time dynamic graphs datasets.

Recommended citation: Karmim, Y., Yang, L., S’Niehotta, R. F., Chatelain, C., Adam, S., & Thome, N. (2024). Temporal receptive field in dynamic graph learning: A comprehensive analysis. ECML-PKDD Machine Learning on Graphs Workshop. https://hal.science/hal-04647025 https://arxiv.org/abs/2407.12370

(NeurIPS2024) Supra-Laplacian Encoding for Transformer on Dynamic Graphs

Published in 38th Conference on Neural Information Processing Systems (NeurIPS 2024), 2024

We design a new spatio-temporal encoding for Dynamic Graph Transformers based on the spectral propreties of its associated supra-laplacian matrix.

Recommended citation: Karmim, Y., Lafon, M., Fournier S’niehotta Cedric, R., & Thome, N. (2024). Supra-Laplacian Encoding for Transformer on Dynamic Graphs. NeurIPS2024. https://arxiv.org/abs/2409.17986v1 https://arxiv.org/abs/2409.17986

talks

teaching

Machine learning teacher for the Wagon.

Training in Machine Learning., Le Wagon, 2021

The wagon is a training organization for the IT professions. I taught machine learning, data science and python courses for different groups.

Teaching assistant for the TRIED Master.

Teaching assistant, CNAM, 2023

At the beginning of 2023 I was teaching assistant for the master in data science TRIED of CNAM. I gave practical classes on deep learning topics with the Keras framework. The website of the course with all the practical works and presentations are available at this link.