10 citations · 30 across the 9 of their papers we have counts for
9 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…
PANDORA: Deep graph learning based COVID-19 infection risk level forecasting
Shuo Yu, Feng Xia, Yueru Wang +3
COVID-19 as a global pandemic causes a massive disruption to social stability that threatens human life and the economy. Policymakers and all elements of society must deliver measu…
Balanced Graph Structure Information for Brain Disease Detection
Falih Gozi Febrinanto, Mujie Liu, Feng Xia
Analyzing connections between brain regions of interest (ROI) is vital to detect neurological disorders such as autism or schizophrenia. Recent advancements employ graph neural net…
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…
Graph Lifelong Learning: A Survey
Falih Gozi Febrinanto, Feng Xia, Kristen Moore +2
Graph learning is a popular approach for performing machine learning on graph-structured data. It has revolutionized the machine learning ability to model graph data to address dow…