Transparency and Privacy: The Role of Explainable AI and Federated Learning in Financial Fraud Detection

20 December 2023

Papers citing "Transparency and Privacy: The Role of Explainable AI and Federated Learning in Financial Fraud Detection"

8 / 8 papers shown

Title
XAI-Driven Client Selection for Federated Learning in Scalable 6G Network Slicing Martino Chiarani Swastika Roy C. Verikoukis Fabrizio Granelli 56 1 0 16 Mar 2025
Non-IID data in Federated Learning: A Survey with Taxonomy, Metrics, Methods, Frameworks and Future Directions Daniel Gutiérrez David Solans Mikko A. Heikkilä A. Vitaletti Nicolas Kourtellis Aris Anagnostopoulos I. Chatzigiannakis OOD 84 0 0 19 Nov 2024
Transforming Triple-Entry Accounting with Machine Learning: A Path to Enhanced Transparency Through Analytics Abraham Itzhak Weinberg Alessio Faccia 65 2 0 19 Nov 2024
Prospects of Privacy Advantage in Quantum Machine Learning Jamie Heredge Niraj Kumar Dylan Herman Shouvanik Chakrabarti Romina Yalovetzky Shree Hari Sureshbabu Changhao Li Marco Pistoia 21 4 0 14 May 2024
Histopathological Image Classification and Vulnerability Analysis using Federated Learning Sankalp Vyas Amar Nath Patra R. Shukla 22 3 0 11 Oct 2023
Federated learning: Applications, challenges and future directions Subrato Bharati Hossain Mondal Prajoy Podder V. B. Surya Prasath FedML 34 52 0 18 May 2022
Towards A Rigorous Science of Interpretable Machine Learning Finale Doshi-Velez Been Kim XAI FaML 225 3,672 0 28 Feb 2017
SMOTE: Synthetic Minority Over-sampling Technique Nitesh V. Chawla Kevin W. Bowyer Lawrence Hall W. Kegelmeyer AI4TS 160 25,214 0 09 Jun 2011