178 citations · 208 across the 13 of their papers we have counts for
7 papers · 1 filter
Leveraging Vulnerabilities in Temporal Graph Neural Networks via Strategic High-Impact Assaults
Dong Hyun Jeon, Lijing Zhu, Haifang Li +6
Temporal Graph Neural Networks (TGNNs) have become indispensable for analyzing dynamic graphs in critical applications such as social networks, communication systems, and financial…
Neuro-Symbolic AI for Cybersecurity: State of the Art, Challenges, and Opportunities
Safayat Bin Hakim, Muhammad Adil, Alvaro Velasquez +2
Cybersecurity demands both rapid pattern recognition and deliberative reasoning, yet purely neural or purely symbolic approaches each address only one side of this duality. Neuro-S…
DEM-NeRF: A Neuro-Symbolic Method for Scientific Discovery through Physics-Informed Simulation
Wenkai Tan, Alvaro Velasquez, Houbing Song
Neural networks have emerged as a powerful tool for modeling physical systems, offering the ability to learn complex representations from limited data while integrating foundationa…
SymRAG: Efficient Neuro-Symbolic Retrieval Through Adaptive Query Routing
Safayat Bin Hakim, Muhammad Adil, Alvaro Velasquez +1
Current Retrieval-Augmented Generation systems use uniform processing, causing inefficiency as simple queries consume resources similar to complex multi-hop tasks. We present SymRA…
xIDS-EnsembleGuard: An Explainable Ensemble Learning-based Intrusion Detection System
Muhammad Adil, Mian Ahmad Jan, Safayat Bin Hakim +2
In this paper, we focus on addressing the challenges of detecting malicious attacks in networks by designing an advanced Explainable Intrusion Detection System (xIDS). The existing…
KGIF: Optimizing Relation-Aware Recommendations with Knowledge Graph Information Fusion
Dong Hyun Jeon, Wenbo Sun, Houbing Herbert Song +4
While deep-learning-enabled recommender systems demonstrate strong performance benchmarks, many struggle to adapt effectively in real-world environments due to limited use of user-…
ANSR-DT: A Neuro-Symbolic Framework for Adaptive and Explainable Digital Twins
Safayat Bin Hakim, Muhammad Adil, Alvaro Velasquez +1
Digital twins are increasingly used to monitor and optimize industrial systems, yet many existing frameworks remain difficult to interpret, slow to adapt, and limited in their abil…