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Detection of Accounting Anomalies in the Latent Space using Adversarial
  Autoencoder Neural Networks

Detection of Accounting Anomalies in the Latent Space using Adversarial Autoencoder Neural Networks

2 August 2019
Marco Schreyer
Timur Sattarov
Christian Schulze
Bernd Reimer
Damian Borth
    AAML
ArXiv (abs)PDFHTML

Papers citing "Detection of Accounting Anomalies in the Latent Space using Adversarial Autoencoder Neural Networks"

14 / 14 papers shown
Diffusion-Scheduled Denoising Autoencoders for Anomaly Detection in Tabular Data
Diffusion-Scheduled Denoising Autoencoders for Anomaly Detection in Tabular Data
Timur Sattarov
Marco Schreyer
Damian Borth
DiffM
183
1
0
01 Aug 2025
Advancing Anomaly Detection: Non-Semantic Financial Data Encoding with
  LLMs
Advancing Anomaly Detection: Non-Semantic Financial Data Encoding with LLMs
A. Bakumenko
Katerina Hlaváčková-Schindler
Claudia Plant
Nina C. Hubig
263
8
0
05 Jun 2024
Fin-Fed-OD: Federated Outlier Detection on Financial Tabular Data
Fin-Fed-OD: Federated Outlier Detection on Financial Tabular Data
Dayananda Herurkar
Sebastián M. Palacio
Ahmed Anwar
J¨orn Hees
Andreas Dengel
FedML
274
6
0
23 Apr 2024
Federated Continual Learning to Detect Accounting Anomalies in Financial
  Auditing
Federated Continual Learning to Detect Accounting Anomalies in Financial Auditing
Marco Schreyer
Hamed Hemati
Damian Borth
M. Vasarhelyi
FedML
264
6
0
26 Oct 2022
Explaining Anomalies using Denoising Autoencoders for Financial Tabular
  Data
Explaining Anomalies using Denoising Autoencoders for Financial Tabular Data
Timur Sattarov
Dayananda Herurkar
Jörn Hees
234
12
0
21 Sep 2022
RESHAPE: Explaining Accounting Anomalies in Financial Statement Audits
  by enhancing SHapley Additive exPlanations
RESHAPE: Explaining Accounting Anomalies in Financial Statement Audits by enhancing SHapley Additive exPlanationsInternational Conference on AI in Finance (ICAF), 2022
Ricardo Müller
Marco Schreyer
Timur Sattarov
Damian Borth
AAMLMLAU
381
10
0
19 Sep 2022
Federated and Privacy-Preserving Learning of Accounting Data in
  Financial Statement Audits
Federated and Privacy-Preserving Learning of Accounting Data in Financial Statement AuditsInternational Conference on AI in Finance (ICAF), 2022
Marco Schreyer
Timur Sattarov
Damian Borth
MLAU
181
26
0
26 Aug 2022
Open ERP System Data For Occupational Fraud Detection
Open ERP System Data For Occupational Fraud Detection
Julian Tritscher
F. Gwinner
Daniel Schlor
Anna Krause
Andreas Hotho
178
9
0
09 Jun 2022
A Combination of Deep Neural Networks and K-Nearest Neighbors for Credit
  Card Fraud Detection
A Combination of Deep Neural Networks and K-Nearest Neighbors for Credit Card Fraud Detection
Dinara Rzayeva
Saber Malekzadeh
97
1
0
27 May 2022
Machine Learning in NextG Networks via Generative Adversarial Networks
Machine Learning in NextG Networks via Generative Adversarial NetworksIEEE Transactions on Cognitive Communications and Networking (IEEE TCCN), 2022
E. Ayanoglu
Kemal Davaslioglu
Y. Sagduyu
GAN
237
44
0
09 Mar 2022
Multi-view Contrastive Self-Supervised Learning of Accounting Data
  Representations for Downstream Audit Tasks
Multi-view Contrastive Self-Supervised Learning of Accounting Data Representations for Downstream Audit TasksInternational Conference on AI in Finance (ICAF), 2021
Marco Schreyer
Timur Sattarov
Damian Borth
MLAU
212
18
0
23 Sep 2021
Learning Sampling in Financial Statement Audits using Vector Quantised
  Autoencoder Neural Networks
Learning Sampling in Financial Statement Audits using Vector Quantised Autoencoder Neural Networks
Marco Schreyer
Timur Sattarov
Anita Gierbl
Bernd Reimer
Damian Borth
DRL
141
3
0
06 Aug 2020
Adversarial Learning of Deepfakes in Accounting
Adversarial Learning of Deepfakes in Accounting
Marco Schreyer
Timur Sattarov
Bernd Reimer
Damian Borth
AAML
188
26
0
09 Oct 2019
Quant GANs: Deep Generation of Financial Time Series
Quant GANs: Deep Generation of Financial Time Series
Magnus Wiese
R. Knobloch
R. Korn
Peter Kretschmer
GANAI4TSAIFin
299
330
0
15 Jul 2019
1
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