39 citations · 130 across the 45 of their papers we have counts for
6 papers · 1 filter
Enhanced Graph Neural Networks with Ego-Centric Spectral Subgraph Embeddings Augmentation
Anwar Said, Mudassir Shabbir, Tyler Derr +2
Graph Neural Networks (GNNs) have shown remarkable merit in performing various learning-based tasks in complex networks. The superior performance of GNNs often correlates with the…
A Survey of Graph Unlearning
Anwar Said, Ngoc N. Tran, Yuying Zhao +4
Graph unlearning emerges as a crucial advancement in the pursuit of responsible AI, providing the means to remove sensitive data traces from trained models, thereby upholding the \…
Learning-Based Heuristic for Combinatorial Optimization of the Minimum Dominating Set Problem using Graph Convolutional Networks
Abihith Kothapalli, Mudassir Shabbir, Xenofon Koutsoukos
A dominating set of a graph is a subset of vertices such that every vertex outside the dominating set is…
NeuroGraph: Benchmarks for Graph Machine Learning in Brain Connectomics
Anwar Said, Roza G. Bayrak, Tyler Derr +4
Machine learning provides a valuable tool for analyzing high-dimensional functional neuroimaging data, and is proving effective in predicting various neurological conditions, psych…
Sequential Graph Neural Networks for Source Code Vulnerability Identification
Ammar Ahmed, Anwar Said, Mudassir Shabbir +1
Vulnerability identification constitutes a task of high importance for cyber security. It is quite helpful for locating and fixing vulnerable functions in large applications. Howev…
Scaling Up 3D Kernels with Bayesian Frequency Re-parameterization for Medical Image Segmentation
Ho Hin Lee, Quan Liu, Shunxing Bao +7
With the inspiration of vision transformers, the concept of depth-wise convolution revisits to provide a large Effective Receptive Field (ERF) using Large Kernel (LK) sizes for med…