Marco Schreyer
Orcid: 0009-0001-3800-2226
According to our database1,
Marco Schreyer
authored at least 17 papers
between 2008 and 2024.
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Bibliography
2024
FedTabDiff: Federated Learning of Diffusion Probabilistic Models for Synthetic Mixed-Type Tabular Data Generation.
CoRR, 2024
2023
Proceedings of the 4th ACM International Conference on AI in Finance, 2023
2022
CoRR, 2022
Federated and Privacy-Preserving Learning of Accounting Data in Financial Statement Audits.
Proceedings of the 3rd ACM International Conference on AI in Finance, 2022
RESHAPE: Explaining Accounting Anomalies in Financial Statement Audits by enhancing SHapley Additive exPlanations.
Proceedings of the 3rd ACM International Conference on AI in Finance, 2022
2021
Continual Learning for Unsupervised Anomaly Detection in Continuous Auditing of Financial Accounting Data.
CoRR, 2021
Multi-view contrastive self-supervised learning of accounting data representations for downstream audit tasks.
Proceedings of the ICAIF'21: 2nd ACM International Conference on AI in Finance, Virtual Event, November 3, 2021
2020
Leaking Sensitive Financial Accounting Data in Plain Sight using Deep Autoencoder Neural Networks.
CoRR, 2020
Learning Sampling in Financial Statement Audits using Vector Quantised Autoencoder Neural Networks.
CoRR, 2020
Learning sampling in financial statement audits using vector quantised variational autoencoder neural networks.
Proceedings of the ICAIF '20: The First ACM International Conference on AI in Finance, 2020
2019
Detection of Accounting Anomalies in the Latent Space using Adversarial Autoencoder Neural Networks.
CoRR, 2019
2017
Detection of Anomalies in Large Scale Accounting Data using Deep Autoencoder Networks.
CoRR, 2017
2010
Proceedings of the Media Forensics and Security II, 2010
2009
Intelligent Printing Technique Recognition and Photocopy Detection for Forensic Document Examination.
Proceedings of the Informatiktage 2009, 2009
Proceedings of the Advances in Digital Forensics V, 2009
2008
Evaluation of Graylevel-Features for Printing Technique Classification in High-Throughput Document Management Systems.
Proceedings of the Computational Forensics, Second International Workshop, 2008