26 citations · 57 across the 13 of their papers we have counts for
5 papers · 1 filter
TopoDetect: Framework for Topological Features Detection in Graph Embeddings
Maroun Haddad, Mohamed Bouguessa
TopoDetect is a Python package that allows the user to investigate if important topological features, such as the Degree of the nodes, their Triangle Count, or their Local Clusteri…
Modeling Regime Shifts in Multiple Time Series
Etienne Gael Tajeuna, Mohamed Bouguessa, Shengrui Wang
We investigate the problem of discovering and modeling regime shifts in an ecosystem comprising multiple time series known as co-evolving time series. Regime shifts refer to the ch…
Rethinking Graph Auto-Encoder Models for Attributed Graph Clustering
Nairouz Mrabah, Mohamed Bouguessa, Mohamed Fawzi Touati +1
Most recent graph clustering methods have resorted to Graph Auto-Encoders (GAEs) to perform joint clustering and embedding learning. However, two critical issues have been overlook…
Exploring the Representational Power of Graph Autoencoder
Maroun Haddad, Mohamed Bouguessa
While representation learning has yielded a great success on many graph learning tasks, there is little understanding behind the structures that are being captured by these embeddi…
Context Matters: Self-Attention for Sign Language Recognition
Fares Ben Slimane, Mohamed Bouguessa
This paper proposes an attentional network for the task of Continuous Sign Language Recognition. The proposed approach exploits co-independent streams of data to model the sign lan…