2027

• T. Repolusk and S. Thonhauser. „Rules and Reconstruction: Stylistic Composition of Song Dynasty Chinese Ci Melodies Using a Variable-Order Markov Model“. In: Journal of Humanistic Mathematics, forthcoming.

2026

• T. Repolusk and E. Veas. „An AI-Powered Assistant for Facilitated Manual Digitization of Historical Chinese Suzipu Notation“. In: Proceedings of the Third Symposium of the ICTMD Study Group on Sound, Movement, and the Sciences (SoMoS). Ed. by L. Pearson, S. Horlor, and R. Caro Repetto. Zenodo, 2026, pp. 70–74. doi: 10.5281/zenodo.21895079
• B. Bauer, T. Repolusk., and S. Krottmaier. „Advanced Layout-Analysis für glossierte Handschriften“. In: digital humanities im deutschsprachigen Raum (DHd 2026). Ed. by S. Schwandt, G. Viehhauser, T. Andrews, and T. Wallnig. Vienna, Austria: University of Vienna, 2026, pp. 434–435. doi: 10.5281/zenodo.18591948

2025

• T. Repolusk and E. Veas. „KuiSCIMA v2.0: Improved Baselines, Calibration, and Cross-Notation Generalization for Historical Chinese Music Notations in Jiang Kui’s Baishidaoren Gequ“. In: Document Analysis and Recognition – ICDAR 2025. Ed. by XC. Yin, D. Karatzas, and D. Lopresti. Cham, Switzerland: Springer Nature Switzerland, 2025, pp. 116–132. doi: 10.1007/978-3-032-04630-7_7

2024

• T. Repolusk and E. Veas. „Semi-Automatic Annotation of Chinese Suzipu Notation Using a Component-Based Prediction and Similarity Approach“. In: Proceedings of the 6th International Workshop on Reading Music Systems (WoRMS). Ed. by J. Calvo-Zaragoza, A. Pacha, and E. Shatri. 2024, pp. 38-42. doi: 10.48550/arXiv.2411.15741.
• T. Repolusk and E. Veas. „The KuiSCIMA Dataset for Optical Music Recognition of Ancient Chinese Suzipu Notation“. In: Document Analysis and Recognition – ICDAR 2024. Ed. by E. H. Barney Smith, M. Liwicki, and L. Peng. Cham, Switzerland: Springer Nature Switzerland, 2024, pp. 38–54. doi: 10.1007/978-3-031-70552-6_3.

2023

• T. Repolusk and E. Veas. „The Suzipu Musical Annotation Tool for the Creation of Machine-Readable Datasets of Ancient Chinese Music“. In: Proceedings of the 5th International Workshop on Reading Music Systems (WoRMS). Ed. by J. Calvo-Zaragoza, A. Pacha, and E. Shatri. Milano, Italy, 2023, pp. 7–11. doi: 10.48550/arXiv.2311.04091.