15 citations · 36 across the 7 of their papers we have counts for
7 papers
Graph Learning
Feng Xia, Ciyuan Peng, Jing Ren +5
Graph learning has rapidly evolved into a critical subfield of machine learning and artificial intelligence (AI). Its development began with early graph-theoretic methods, gaining…
Rehearsal with Auxiliary-Informed Sampling for Audio Deepfake Detection
Falih Gozi Febrinanto, Kristen Moore, Chandra Thapa +3
The performance of existing audio deepfake detection frameworks degrades when confronted with new deepfake attacks. Rehearsal-based continual learning (CL), which updates models us…
SIGNL: A Label-Efficient Audio Deepfake Detection System via Spectral-Temporal Graph Non-Contrastive Learning
Falih Gozi Febrinanto, Kristen Moore, Chandra Thapa +2
Audio deepfake detection is increasingly important as synthetic speech becomes more realistic and accessible. Recent methods, including those using graph neural networks (GNNs) to…
Prompt Learning for Multi-Label Code Smell Detection: A Promising Approach
Haiyang Liu, Yang Zhang, Vidya Saikrishna +2
Code smells indicate the potential problems of software quality so that developers can identify refactoring opportunities by detecting code smells. State-of-the-art approaches leve…
Deep Outdated Fact Detection in Knowledge Graphs
Huiling Tu, Shuo Yu, Vidya Saikrishna +2
Knowledge graphs (KGs) have garnered significant attention for their vast potential across diverse domains. However, the issue of outdated facts poses a challenge to KGs, affecting…
Entropy Causal Graphs for Multivariate Time Series Anomaly Detection
Falih Gozi Febrinanto, Kristen Moore, Chandra Thapa +4
Many multivariate time series anomaly detection frameworks have been proposed and widely applied. However, most of these frameworks do not consider intrinsic relationships between…
Physics-Informed Graph Learning
Ciyuan Peng, Feng Xia, Vidya Saikrishna +1
An expeditious development of graph learning in recent years has found innumerable applications in several diversified fields. Of the main associated challenges are the volume and…