Feature Transformation Enhanced Jacobi Polynomial Graph Filtering for Graph Anomaly Detection

arXiv:2608.27144 · cs.AI · Submitted 2026-08-27 · Read on arXiv

cs.AI

Submitted: 2026-08-27

Updated: 2026-08-27

Terminology

• AUC — 41× in this paper · explained in 2 episodes
• GNNs — 14× in this paper · explained in 2 episodes
• Consistency — 10× in this paper · explained in 3 episodes
• Aggregation — 5× in this paper · explained in 1 episode
• Adaptive Graph — 4× in this paper · explained in 1 episode
• Attention Mechanism — 4× in this paper · explained in 2 episodes
• Embeddings — 4× in this paper · explained in 2 episodes
• Representation Learning — 4× in this paper · explained in 2 episodes
• Ablation — 3× in this paper · explained in 1 episode
• Chebyshev Polynomials — 3× in this paper · explained in 2 episodes
• Cosine Similarity — 3× in this paper · explained in 3 episodes
• Loss Function — 3× in this paper · explained in 2 episodes
• Ablation study — 2× in this paper · explained in 1 episode
• Accuracy — 2× in this paper · explained in 1 episode
• Heterogeneous Graph — 2× in this paper · explained in 2 episodes
• Hypergraph — 2× in this paper · explained in 2 episodes
• Adaptability — 1× in this paper · explained in 1 episode
• Adaptation — 1× in this paper · explained in 1 episode
• Adjacency Matrix — 1× in this paper · explained in 1 episode
• Benchmarking — 1× in this paper · explained in 3 episodes
• Computational overhead — 1× in this paper · explained in 2 episodes
• Data Augmentation — 1× in this paper · explained in 7 episodes
• Distribution Shift — 1× in this paper · explained in 5 episodes
• Generalization — 1× in this paper · explained in 13 episodes
• Graph Neural Networks (GNNs) — 1× in this paper · explained in 7 episodes
• Homogeneity — 1× in this paper · explained in 2 episodes
• Knowledge Graph — 1× in this paper · explained in 7 episodes
• Knowledge graphs — 1× in this paper · explained in 2 episodes
• Latent Space — 1× in this paper · explained in 7 episodes

Sources

• Anti-Money Laundering in Bitcoin: Experimenting with Graph Convolutional Networks for Financial Forensics

Related papers

• MAVEN-T: Reinforced Heterogeneous Distillation for Real-Time Multi-Agent Trajectory Prediction
• Model Discovery Agent: LLM-assisted Bayesian experiment design for data-efficient discovery of mechanistic world models
• The Clinician's Veto: Navigating Trust, Liability, and Uncertainty in Autonomous AI Prescribing
• MindHelper: Closed-Loop Embodied Mental-State Reasoning for Precision Intervention
• Incumbent Advantage: Brand Bias and Cognitive Manipulation Dynamics in LLM Recommendation Systems
• VSAL: A Vision Solver with Adaptive Layouts for Graph Property Detection