I am a PhD Candidate in Artificial Intelligence at Institut Polytechnique de Paris (Télécom Paris), under the supervision of Thomas Bonald (LTCI – Information Processing and Communications Laboratory, Télécom Paris) and Tiphaine Viard, (i3 – Interdisciplinary Institute of Innovation, Télécom Paris).
In my research, I study enriched graph methods and algorithms to leverage information from real-world data, in order to add transparency in current machine learning approaches.
My research interests include:
- Real-world graphs
- Graph algorithms
- Fairness and ethics in AI
- Graph Neural Networks
Research
PUBLICATIONS
Graph Neural Networks: The Surprising Superiority of Logistic Regression
Simon Delarue, Thomas Bonald, Tiphaine Viard
[Under review]
Sparse Graph Neural Networks with Scikit-network
Simon Delarue, Thomas Bonald
International Conference on Complex Networks and their Applications, 2023
Unexpected Attributed Subgraphs: a Mining Algorithm
Simon Delarue, Tiphaine Viard, Jean-Louis Dessalles
IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, 2023
TALKS
HI!PARIS READING GROUP ON GRAPH NEURAL NETWORKS, 2022
Representation Learning on large graphs (with Thomas Bonald)
Ressource material
INSTITUT POLYTECHNIQUE DE PARIS DOCTORAL SCHOOL DAY, 2022
“Unexpected attributed subgraphs: a mining algorithm” (Best poster award in the field of Computing, Data and Artificial Intelligence)
Poster
HI!PARIS SUMMER SCHOOL, 2022
“Sparse Graph Neural Networks” (Best poster award)
Poster