IEEE

Using Graph Attention Networks in Healthcare Provider Fraud Detection

Abstract: Healthcare fraud increases healthcare expenses for insurers, premiums for policyholders, and dissatisfaction of legitimate patients and causes severe damage to the health system. Therefore, ...
IEEE

Examining IoT-Based Smart Campus Adoption Model: An Investigation Using Two-Stage Analysis Comprising Structural Equation Modelling and Artificial Neural Network

Abstract: The progress and evolution of technology have been rapidly transforming various aspects of our society and daily lives, including colleges and campuses into smarter environments compared to ...
IEEE

New Approaches for Network Topology Optimization Using Deep Reinforcement Learning and Graph Neural Network

Abstract: The exponential growth in Internet-connected devices has escalated the demand for optimized network topologies to ensure high performance. Traditional optimization methods often fall short ...
IEEE

A Graph Representation Learning Approach for Imbalanced Ship Type Recognition Using AIS Trajectory Data

Abstract: Marine transportation constitutes a vital segment of international trade logistics. Recognizing marine carrier ship types is essential for the governance and efficiency of the marine ...
IEEE

Propagating Uncertainty in Power System Initial Conditions Using Data-Driven Linear Operators

Abstract: In this paper, we propose a data-driven approach for uncertainty moment propagation through the non-linear power system dynamics. The proposed approach relies on the linear representation of ...
IEEE

Graph Transformer Geometric Learning of Brain Networks Using Multimodal MR Images for Brain Age Estimation

Abstract: Brain age is considered as an important biomarker for detecting aging-related diseases such as Alzheimer’s Disease (AD). Magnetic resonance imaging (MRI) have been widely investigated with ...
IEEE

PGDTA: Predicting Drug-Target Affinity Using Three-Dimensional Structure of Protein Pocket and Graph Neural Network

Abstract: Drug-Target Affinity (DTA) prediction plays a crucial role in drug discovery, and accurate DTA prediction can significantly reduce the cost of drug development. While most studies focus on ...
GitHub

Are You Using Reliable Graph Prompts? Trojan Prompt Attacks on Graph Neural Networks

This is the official implementation of "Are You Using Reliable Graph Prompts? Trojan Prompt Attacks on Graph Neural Networks". (KDD 2025) If you find this repo to be useful, please cite our paper.
IEEE

Cyber threat response using reinforcement learning in graph-based attack simulations

Abstract: In this ongoing project we employ reinforcement learning in a simulation environment to learn policies for cyber defense. The environment is based on attack graphs produced using the Meta ...
IEEE

Using Bipartite Graph Embedding and Deep Learning Method Predicting RNA Protein Interactions

Abstract: RNA-protein interaction (RPI) play an important role in biological activities. Using deep learning techniques to predict RPI can not only process complex data, but also obtain accurate ...
IEEE

Alarm Root-Cause Analysis Using an Alarm Logic Directed Graph Extracted From Control Software

Abstract: The growing complexity of modern automated production systems demands solutions for managing alarm floods potentially stemming from multi-root causes, while improving situational awareness ...
GitHub

Biconjugate Gradient Stabilized Algorithm

The goal of this assignment was to develop a program in C that is capable of solving first-order linear systems of equations. These systems are of the form Ax=b, where A is a known matrix, b is a ...