39 citations · 130 across the 45 of their papers we have counts for
6 papers · 1 filter
Defining and Benchmarking a Data-Centric Design Space for Brain Graph Construction
Qinwen Ge, Roza G. Bayrak, Anwar Said +3
The construction of brain graphs from functional Magnetic Resonance Imaging (fMRI) data plays a crucial role in enabling graph machine learning for neuroimaging. However, current p…
Evaluating Out-of-Distribution Robustness in Graph-Based Android Malware Classification: A New Principled Benchmark
Ngoc N. Tran, Anwar Said, Waseem Abbas +2
While graph-based Android malware classifiers report strong benchmark accuracy of over 94%, their performance sharply decreases up to 45% when exposed to previously unseen variants…
Feature Construction Using Network Control Theory and Rank Encoding for Graph Machine Learning
Anwar Said, Yifan Wei, Obaid Ullah Ahmad +3
In this article, we utilize the concept of average controllability in graphs, along with a novel rank encoding method, to enhance the performance of Graph Neural Networks (GNNs) in…
Robust Anomaly Detection with Graph Neural Networks using Controllability
Yifan Wei, Anwar Said, Waseem Abbas +1
Anomaly detection in complex domains poses significant challenges due to the need for extensive labeled data and the inherently imbalanced nature of anomalous versus benign samples…
An upper bound on generalized cospectral mates of oriented hraphs using skew-walk matrices
Muhammad Raza, Obaid Ullah Ahmed, Mudassir Shabbir +2
Let be an oriented graph with skew-adjacency matrix . Two oriented graphs and are said to share the same generalized skew spectrum if and have the s…
Learning Backbones: Sparsifying Graphs through Zero Forcing for Effective Graph-Based Learning
Obaid Ullah Ahmad, Anwar Said, Mudassir Shabbir +2
This paper introduces a novel framework for graph sparsification that preserves the essential learning attributes of original graphs, improving computational efficiency and reducin…