Detection of Anomalies in Large Scale Accounting Data using Deep Autoencoder Networks

15 September 2017

Papers citing "Detection of Anomalies in Large Scale Accounting Data using Deep Autoencoder Networks"

9 / 9 papers shown

Title
Federated Continual Learning to Detect Accounting Anomalies in Financial Auditing Marco Schreyer Hamed Hemati Damian Borth M. Vasarhelyi FedML 42 3 0 26 Oct 2022
Explaining Anomalies using Denoising Autoencoders for Financial Tabular Data Timur Sattarov Dayananda Herurkar Jörn Hees 30 8 0 21 Sep 2022
RESHAPE: Explaining Accounting Anomalies in Financial Statement Audits by enhancing SHapley Additive exPlanations Ricardo Müller Marco Schreyer Timur Sattarov Damian Borth AAML MLAU 26 7 0 19 Sep 2022
Federated and Privacy-Preserving Learning of Accounting Data in Financial Statement Audits Marco Schreyer Timur Sattarov Damian Borth MLAU 33 15 0 26 Aug 2022
Multi-view Contrastive Self-Supervised Learning of Accounting Data Representations for Downstream Audit Tasks Marco Schreyer Timur Sattarov Damian Borth MLAU 32 15 0 23 Sep 2021
SSD: A Unified Framework for Self-Supervised Outlier Detection Vikash Sehwag M. Chiang Prateek Mittal OODD 31 330 0 22 Mar 2021
Detecting Anomalous Invoice Line Items in the Legal Case Lifecycle V. Constantinou M. Kabiri AILaw 18 2 0 28 Dec 2020
Quant GANs: Deep Generation of Financial Time Series Magnus Wiese R. Knobloch R. Korn Peter Kretschmer GAN AI4TS AIFin 22 273 0 15 Jul 2019
Improving neural networks by preventing co-adaptation of feature detectors Geoffrey E. Hinton Nitish Srivastava A. Krizhevsky Ilya Sutskever Ruslan Salakhutdinov VLM 266 7,636 0 03 Jul 2012