Copertina

Explainable Graph Neural Networks for Interbank Contagion Surveillance: A Regulatory-Aligned Framework for the U.S. Banking Sector

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autore principale:	Uddin, Mohammad Nasir
Natura:	Preprint
Pubblicazione:	2026
Soggetti:	Machine Learning Artificial Intelligence
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

A Regulatory Governance Framework for AI-Driven Financial Fraud Detection in U.S. Banking: Integrating OCC, SR 11-7, CFPB, and FinCEN Compliance Requirements for Model Development, Validation, and Monitoring Lifecycles
di: Uddin, Mohammad Nasir
Pubblicazione: (2026)

SCAFDS: Edge-Feature Graph Attention for Interbank Fraud Detection with Attribution-Grounded SAR Generation
di: Uddin, Mohammad Nasir
Pubblicazione: (2026)

Shapley Value-Guided Adaptive Ensemble Learning for Explainable Financial Fraud Detection with U.S. Regulatory Compliance Validation
di: Uddin, Mohammad Nasir, et al.
Pubblicazione: (2026)

Evaluating Neighbor Explainability for Graph Neural Networks
di: Llorente, Oscar, et al.
Pubblicazione: (2023)

Explainable Graph Neural Networks Under Fire
di: Li, Zhong, et al.
Pubblicazione: (2024)

Parallelizing Node-Level Explainability in Graph Neural Networks
di: Llorente, Oscar, et al.
Pubblicazione: (2026)

GraphFramEx: Towards Systematic Evaluation of Explainability Methods for Graph Neural Networks
di: Amara, Kenza, et al.
Pubblicazione: (2022)

Explainable Global Wildfire Prediction Models using Graph Neural Networks
di: Chen, Dayou, et al.
Pubblicazione: (2024)

SES: Bridging the Gap Between Explainability and Prediction of Graph Neural Networks
di: Huang, Zhenhua, et al.
Pubblicazione: (2024)

Prediction of Bank Credit Ratings using Heterogeneous Topological Graph Neural Networks
di: Liu, Junyi, et al.
Pubblicazione: (2025)

Quantum Topological Graph Neural Networks for Detecting Complex Fraud Patterns
di: Doost, Mohammad, et al.
Pubblicazione: (2025)

GNN-XAR: A Graph Neural Network for Explainable Activity Recognition in Smart Homes
di: Fiori, Michele, et al.
Pubblicazione: (2025)

FlowX: Towards Explainable Graph Neural Networks via Message Flows
di: Gui, Shurui, et al.
Pubblicazione: (2022)

Graph Attention Networks Unleashed: A Fast and Explainable Vulnerability Assessment Framework for Microgrids
di: Liu, Wei, et al.
Pubblicazione: (2025)

Aligning Knowledge Graphs Provided by Humans and Generated from Neural Networks in Specific Tasks
di: Li, Tangrui, et al.
Pubblicazione: (2024)

An Explainable Transformer-based Model for Phishing Email Detection: A Large Language Model Approach
di: Uddin, Mohammad Amaz, et al.
Pubblicazione: (2024)

Deeply Explainable Artificial Neural Network
di: Zucker, David
Pubblicazione: (2025)

Cross-Attention Graph Neural Networks for Inferring Gene Regulatory Networks with Skewed Degree Distribution
di: Xiong, Jiaqi, et al.
Pubblicazione: (2024)

From Text to Graph: Leveraging Graph Neural Networks for Enhanced Explainability in NLP
di: Yáñez-Romero, Fabio, et al.
Pubblicazione: (2025)

An Explainable Disease Surveillance System for Early Prediction of Multiple Chronic Diseases
di: Khan, Shaheer Ahmad, et al.
Pubblicazione: (2025)

A General Benchmark Framework is Dynamic Graph Neural Network Need
di: Zhang, Yusen
Pubblicazione: (2024)

STM-Graph: A Python Framework for Spatio-Temporal Mapping and Graph Neural Network Predictions
di: Ghaffari, Amirhossein, et al.
Pubblicazione: (2025)

An Explainable Ensemble Learning Framework for Crop Classification with Optimized Feature Pyramids and Deep Networks
di: Masud, Syed Rayhan, et al.
Pubblicazione: (2026)

Compressing Deep Neural Networks Using Explainable AI
di: Soroush, Kimia, et al.
Pubblicazione: (2025)

Atherosclerosis through Hierarchical Explainable Neural Network Analysis
di: Adam, Irsyad, et al.
Pubblicazione: (2025)

Self-Pro: A Self-Prompt and Tuning Framework for Graph Neural Networks
di: Gong, Chenghua, et al.
Pubblicazione: (2023)

An Explainable Failure Prediction Framework for Neural Networks in Radio Access Networks
di: Papry, Khaleda, et al.
Pubblicazione: (2026)

Enhancing Explainability of Graph Neural Networks Through Conceptual and Structural Analyses and Their Extensions
di: Bui, Tien Cuong
Pubblicazione: (2025)

Breast Cancer Diagnosis: A Comprehensive Exploration of Explainable Artificial Intelligence (XAI) Techniques
di: Bai, Samita, et al.
Pubblicazione: (2024)

Framework GNN-AID: Graph Neural Network Analysis Interpretation and Defense
di: Lukyanov, Kirill, et al.
Pubblicazione: (2025)

LOGIN: A Large Language Model Consulted Graph Neural Network Training Framework
di: Qiao, Yiran, et al.
Pubblicazione: (2024)

EEG-Based Consumer Behaviour Prediction: An Exploration from Classical Machine Learning to Graph Neural Networks
di: Afshar, Mohammad Parsa, et al.
Pubblicazione: (2025)

Graph Computation Meets Circuit Algebra: A Task-Aligned Analysis of Graph Neural Networks for Electronic Design Automation
di: Kim, Hyunmog
Pubblicazione: (2026)

Regulatory Graphs and GenAI for Real-Time Transaction Monitoring and Compliance Explanation in Banking
di: Khanvilkar, Kunal, et al.
Pubblicazione: (2025)

Graphs Unveiled: Graph Neural Networks and Graph Generation
di: Kovács, László, et al.
Pubblicazione: (2024)

Graph Neural Networks for Learning Equivariant Representations of Neural Networks
di: Kofinas, Miltiadis, et al.
Pubblicazione: (2024)

PSO-XAI: A PSO-Enhanced Explainable AI Framework for Reliable Breast Cancer Detection
di: Raquib, Mirza, et al.
Pubblicazione: (2025)

Commute Graph Neural Networks
di: Zhuo, Wei, et al.
Pubblicazione: (2024)

Cooperative Graph Neural Networks
di: Finkelshtein, Ben, et al.
Pubblicazione: (2023)

Superposition in Graph Neural Networks
di: Pertl, Lukas, et al.
Pubblicazione: (2025)