DOAJ
open access
Prediction of bank transaction fraud using TabNet—an adaptive deep learning architecture
Conceptio Open Archive
Analyze & explore related research in Conceptio
Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.
This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗
Related documents
- Scalable and Verifiable Federated Learning for Cross-Institution Financial Fraud Detection#138867
- Leveraging artificial intelligence for enhanced anti-money laundering in financial institutions#145126
- The TELLER Dataset#422527
- Quantum Kernel k-Means for Credit-Card Fraud Detection:A Controlled Benchmark on Real Transaction Data#616861
- Quantum Kernel k-Means for Credit-Card Fraud Detection:A Controlled Benchmark on Real Transaction Data#616361
Record · ID 20073
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive