Timur Sattarov

Publication Activity (10 Years)

Years Active: 2017-2024
Publications (10 Years): 16

Top Topics

Diffusion Models

Supervised Learning

Top Venues

Publications

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