1 citations · 2 across the 2 of their papers we have counts for
5 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…
Refined Causal Graph Structure Learning via Curvature for Brain Disease Classification
Falih Gozi Febrinanto, Adonia Simango, Chengpei Xu +4
Graph neural networks (GNNs) have been developed to model the relationship between regions of interest (ROIs) in brains and have shown significant improvement in detecting brain di…
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…
GraphDART: Graph Distillation for Efficient Advanced Persistent Threat Detection
Saba Fathi Rabooki, Bowen Li, Falih Gozi Febrinanto +4
Cyber-physical-social systems (CPSSs) have emerged in many applications over recent decades, requiring increased attention to security concerns. The rise of sophisticated threats l…
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…