Timur Sattarov

21 papers B 1Journal 13Unranked 7

Year	Rank	Type	Title / Venue / Authors
2025	—	`conf`	Diffusion-Scheduled Denoising Autoencoders for Anomaly Detection in Tabular Data. KDD (2) Timur Sattarov, Marco Schreyer, Damian Borth
2025	J	`jnl`	Diffusion-Scheduled Denoising Autoencoders for Anomaly Detection in Tabular Data. CoRR Timur Sattarov, Marco Schreyer, Damian Borth
2025	J	`jnl`	Privacy Preserving Diffusion Models for Mixed-Type Tabular Data Generation. CoRR Timur Sattarov, Marco Schreyer, Damian Borth
2024	J	`jnl`	Differentially Private Federated Learning of Diffusion Models for Synthetic Tabular Data Generation. CoRR Timur Sattarov, Marco Schreyer, Damian Borth
2024	J	`jnl`	FedTabDiff: Federated Learning of Diffusion Probabilistic Models for Synthetic Mixed-Type Tabular Data Generation. CoRR Timur Sattarov, Marco Schreyer, Damian Borth
2024	—	`conf`	Imb-FinDiff: Conditional Diffusion Models for Class Imbalance Synthesis of Financial Tabular Data. ICAIF Marco Schreyer, Timur Sattarov, Alexander Sim, Kesheng Wu
2023	B	`conf`	Cross-Domain Transformation for Outlier Detection on Tabular Datasets. IJCNN Dayananda Herurkar, Timur Sattarov, Jörn Hees, Sebastian Palacio, Federico Raue, Andreas Dengel
2023	—	`conf`	FinDiff: Diffusion Models for Financial Tabular Data Generation. ICAIF Timur Sattarov, Marco Schreyer, Damian Borth
2023	J	`jnl`	FinDiff: Diffusion Models for Financial Tabular Data Generation. CoRR Timur Sattarov, Marco Schreyer, Damian Borth
2022	J	`jnl`	Explaining Anomalies using Denoising Autoencoders for Financial Tabular Data. CoRR Timur Sattarov, Dayananda Herurkar, Jörn Hees
2022	—	`conf`	Federated and Privacy-Preserving Learning of Accounting Data in Financial Statement Audits. ICAIF Marco Schreyer, Timur Sattarov, Damian Borth
2022	J	`jnl`	Federated and Privacy-Preserving Learning of Accounting Data in Financial Statement Audits. CoRR Marco Schreyer, Timur Sattarov, Damian Borth
2022	—	`conf`	RESHAPE: Explaining Accounting Anomalies in Financial Statement Audits by enhancing SHapley Additive exPlanations. ICAIF Ricardo Müller, Marco Schreyer, Timur Sattarov, Damian Borth
2022	J	`jnl`	RESHAPE: Explaining Accounting Anomalies in Financial Statement Audits by enhancing SHapley Additive exPlanations. CoRR Ricardo Müller, Marco Schreyer, Timur Sattarov, Damian Borth
2021	J	`jnl`	Multi-view Contrastive Self-Supervised Learning of Accounting Data Representations for Downstream Audit Tasks. CoRR Marco Schreyer, Timur Sattarov, Damian Borth
2021	—	`conf`	Multi-view contrastive self-supervised learning of accounting data representations for downstream audit tasks. ICAIF Marco Schreyer, Timur Sattarov, Damian Borth
2020	J	`jnl`	Learning Sampling in Financial Statement Audits using Vector Quantised Autoencoder Neural Networks. CoRR Marco Schreyer, Timur Sattarov, Anita Gierbl, Bernd Reimer, Damian Borth
2020	—	`conf`	Learning sampling in financial statement audits using vector quantised variational autoencoder neural networks. ICAIF Marco Schreyer, Timur Sattarov, Anita Gierbl, Bernd Reimer, Damian Borth
2019	J	`jnl`	Adversarial Learning of Deepfakes in Accounting. CoRR Marco Schreyer, Timur Sattarov, Bernd Reimer, Damian Borth
2019	J	`jnl`	Detection of Accounting Anomalies in the Latent Space using Adversarial Autoencoder Neural Networks. CoRR Marco Schreyer, Timur Sattarov, Christian Schulze, Bernd Reimer, Damian Borth
2017	J	`jnl`	Detection of Anomalies in Large Scale Accounting Data using Deep Autoencoder Networks. CoRR Marco Schreyer, Timur Sattarov, Damian Borth, Andreas Dengel, Bernd Reimer