Detection of Anomalies in Large Scale Accounting Data using Deep Autoencoder Networks. - Marco Schreyer; Timur Sattarov; Damian Borth; Andreas Dengel 001; Bernd Reimer (CoRR, 2017)

Detection of Accounting Anomalies in the Latent Space using Adversarial Autoencoder Neural Networks. - Marco Schreyer; Timur Sattarov; Christian Schulze 001; Bernd Reimer; Damian Borth (CoRR, 2019)

Adversarial Learning of Deepfakes in Accounting. - Marco Schreyer; Timur Sattarov; Bernd Reimer; Damian Borth (CoRR, 2019)

Learning sampling in financial statement audits using vector quantised variational autoencoder neural networks. - Marco Schreyer; Timur Sattarov; Anita Gierbl; Bernd Reimer; Damian Borth (ICAIF, 2020)

Learning Sampling in Financial Statement Audits using Vector Quantised Autoencoder Neural Networks. - Marco Schreyer; Timur Sattarov; Anita Gierbl; Bernd Reimer; Damian Borth (CoRR, 2020)

Multi-view contrastive self-supervised learning of accounting data representations for downstream audit tasks. - Marco Schreyer; Timur Sattarov; Damian Borth (ICAIF, 2021)

RESHAPE: Explaining Accounting Anomalies in Financial Statement Audits by enhancing SHapley Additive exPlanations. - Ricardo Müller; Marco Schreyer; Timur Sattarov; Damian Borth (ICAIF, 2022)

Federated and Privacy-Preserving Learning of Accounting Data in Financial Statement Audits. - Marco Schreyer; Timur Sattarov; Damian Borth (ICAIF, 2022)

Explaining Anomalies using Denoising Autoencoders for Financial Tabular Data. - Timur Sattarov; Dayananda Herurkar; Jörn Hees (CoRR, 2022)

FinDiff: Diffusion Models for Financial Tabular Data Generation. - Timur Sattarov; Marco Schreyer; Damian Borth (ICAIF, 2023)

Cross-Domain Transformation for Outlier Detection on Tabular Datasets. - Dayananda Herurkar; Timur Sattarov; Jörn Hees; Sebastian Palacio; Federico Raue; Andreas Dengel 001 (IJCNN, 2023)

Imb-FinDiff: Conditional Diffusion Models for Class Imbalance Synthesis of Financial Tabular Data. - Marco Schreyer; Timur Sattarov; Alexander Sim; Kesheng Wu (ICAIF, 2024)

FedTabDiff: Federated Learning of Diffusion Probabilistic Models for Synthetic Mixed-Type Tabular Data Generation. - Timur Sattarov; Marco Schreyer; Damian Borth (CoRR, 2024)

Differentially Private Federated Learning of Diffusion Models for Synthetic Tabular Data Generation. - Timur Sattarov; Marco Schreyer; Damian Borth (CoRR, 2024)

Diffusion-Scheduled Denoising Autoencoders for Anomaly Detection in Tabular Data. - Timur Sattarov; Marco Schreyer; Damian Borth (CoRR, 2025)