- 👀 I’m interested in programming & math.
- 🌱 I’m currently learning TDA.
- 💞️ I’m looking to collaborate on ML.
- 📫 How to reach me? E-mail.
📗 CV
- Luciano Melodia (2024): Algebraic and Topological Persistence. Bachelor Thesis, Friedrich-Alexander Universität Erlangen-Nürnberg.
- Luciano Melodia (2023): Notes on Simplicial and Singular Homology. Seminar Topics in Topology, Friedrich-Alexander Universität Erlangen-Nürnberg.
- Luciano Melodia and Richard Lenz (2022): Homological Time Series Analysis of Sensor Signals from Power Plants. Machine Learning for Irregular Time Series. Machine Learning and Principles and Practice of Knowledge Discovery in Databases. In Michael Kamp, Irena Koprinska, Adrien Bibal et al. (ed.): Communications in Computer and Information Science. Springer Nature, Switzerland.
- Luciano Melodia and Richard Lenz(2021): Estimate of the Neural Network Dimension Using Algebraic Topology and Lie Theory. Image Mining. Theory and Applications VII. Pattern Recognition and Information Forensics. In Alberto Del Bimbo, Rita Cucchiara, Stan Sciaroff et al. (ed.): Lecture Notes in Computer Science. Springer Nature, Switzerland
- Luciano Melodia and Richard Lenz (2020): Persistent Homology as Stopping-Criterion for Voronoi Interpolation. Proceedings of the International Workshop on Combinatorial Image Analysis. In Tibor Lukić, Reneta Barneva, Valentin Brimkov et al. (ed.): Lecture Notes in Computer Science. Springer, Cham.
- Luciano Melodia (2016): Deep Learning Schätzung zur absorbierten Strahlungsdosis für die nuklearmedizinische Diagnostik. Library of the University of Regensburg, Master Thesis in Information Science.
- Luciano Melodia (2015): Zur Verwendung des Paradigmas brauchen mit und ohne zu mit Infinitiv. In Katešina Šichovà, Reinhard Krapp, Rössler Paul et al. (ed.): Standardvarietät des Deutschen – Fallbeispiele aus der sozialen Praxis, Logos, Berlin.