3 papers
cs.GR2026
Random-Forest-Induced Graph Neural Networks for Tabular Learning
Haozhe Chen, Soheila Farokhi, Kelvyn Bladen +2
Graphs are essential for modeling complex relationships and capturing structured interactions in data. Graph Neural Networks (GNNs) are particularly effective when such relational…
cs.LG2025
TAWRMAC: A Novel Dynamic Graph Representation Learning Method
Soheila Farokhi, Xiaojun Qi, Hamid Karimi
Dynamic graph representation learning has become essential for analyzing evolving networks in domains such as social network analysis, recommendation systems, and traffic analysis.…
cs.LG2023
Enhancing the Performance of Automated Grade Prediction in MOOC using Graph Representation Learning
Soheila Farokhi, Aswani Yaramala, Jiangtao Huang +3
In recent years, Massive Open Online Courses (MOOCs) have gained significant traction as a rapidly growing phenomenon in online learning. Unlike traditional classrooms, MOOCs offer…