All Stories

  1. Diffusion-Scheduled Denoising Autoencoders for Anomaly Detection in Tabular Data

    Article • August 2025, ACM (Association for Computing Machinery)

    Marco Schreyer

  2. Imb-FinDiff: Conditional Diffusion Models for Class Imbalance Synthesis of Financial Tabular Data

    Article • November 2024, ACM (Association for Computing Machinery)

    Marco Schreyer, Alex Sim

  3. FinDiff: Diffusion Models for Financial Tabular Data Generation

    Article • November 2023, ACM (Association for Computing Machinery)

    Marco Schreyer, Timur Sattarov

  4. Federated and Privacy-Preserving Learning of Accounting Data in Financial Statement Audits

    Article • October 2022, ACM (Association for Computing Machinery)

    Marco Schreyer

  5. Explaining Accounting Anomalies by enhancing SHapley Additive exPlanations

    Article • October 2022, ACM (Association for Computing Machinery)

    Marco Schreyer, Ricardo Müller, Timur Sattarov

  6. Multi-view contrastive self-supervised learning of accounting data representations for downstream audit tasks

    Article • November 2021, ACM (Association for Computing Machinery)

    Marco Schreyer

  7. Learning sampling in financial statement audits using vector quantised variational autoencoder neural networks

    Article • October 2020, ACM (Association for Computing Machinery)

    Marco Schreyer