1 citations · 1 across the 2 of their papers we have counts for
3 papers
cs.LG2022
Are Graph Representation Learning Methods Robust to Graph Sparsity and Asymmetric Node Information?
Pierre Sevestre, Marine Neyret
The growing popularity of Graph Representation Learning (GRL) methods has resulted in the development of a large number of models applied to a miscellany of domains. Behind this di…
cs.LG2020★ 1 cited
About Graph Degeneracy, Representation Learning and Scalability
Simon Brandeis, Adrian Jarret, Pierre Sevestre
Graphs or networks are a very convenient way to represent data with lots of interaction. Recently, Machine Learning on Graph data has gained a lot of traction. In particular, verte…
cs.CV2019
A*3D Dataset: Towards Autonomous Driving in Challenging Environments
Quang-Hieu Pham, Pierre Sevestre, Ramanpreet Singh Pahwa +6
With the increasing global popularity of self-driving cars, there is an immediate need for challenging real-world datasets for benchmarking and training various computer vision tas…