Yannick Rudolph
- Business informatics
- Informatics
Research areas
1 - 7 out of 7Page size: 10
- 2025
- E-pub ahead of print
Self-improvement for Computerized Adaptive Testing
Rudolph, Y., Neubauer, K. & Brefeld, U., 2026, Machine Learning and Knowledge Discovery in Databases - Research Track: European Conference, ECML PKDD 2025, Porto, Portugal, September 15–19, 2025, Proceedings. Ribeiro, R. P., Jorge, A. M., Soares, C., Gama, J., Pfahringer, B., Japkowicz, N., Larrañaga, P. & Abreu, P. H. (eds.). Cham: Springer International Publishing, Vol. 2. p. 70-86 17 p. (Lecture Notes in Computer Science; vol. 16014 LNCS).Research output: Contributions to collected editions/works › Article in conference proceedings › Research › peer-review
- Published
Masked autoencoder for multiagent trajectories
Rudolph, Y. & Brefeld, U., 02.2025, In: Machine Learning. 114, 2, 18 p., 44.Research output: Journal contributions › Journal articles › Research › peer-review
- 2024
- Published
Masked Autoencoder Pretraining for Event Classification in Elite Soccer
Rudolph, Y. & Brefeld, U., 26.02.2024, Machine Learning and Data Mining for Sports Analytics: 10th International Workshop, MLSA 2023, Revised Selected Papers. Brefeld, U., Davis, J., Van Haaren, J. & Zimmermann, A. (eds.). Cham: Springer Nature Switzerland AG, p. 24-35 12 p. (Communications in Computer and Information Science; vol. 2035).Research output: Contributions to collected editions/works › Article in conference proceedings › Research › peer-review
- 2023
- Published
Convolutional Neural Networks
Rudolph, Y. & Brefeld, U., 01.01.2023, Sportinformatik: Modellbildung, Simulation, Datenanalyse und Visualisierung von sportbezogenen Daten. Memmert, D. (ed.). Berlin: Springer Spektrum, p. 207-215 9 p.Research output: Contributions to collected editions/works › Chapter
- 2022
- Published
Modeling Conditional Dependencies in Multiagent Trajectories
Rudolph, Y. & Brefeld, U., 2022, In: Proceedings of Machine Learning Research. 151, p. 10518-10533 16 p.Research output: Journal contributions › Conference article in journal › Research › peer-review
- 2020
- Published
Graph Conditional Variational Models: Too Complex for Multiagent Trajectories?
Rudolph, Y., Brefeld, U. & Dick, U., 2020, In: Proceedings of Machine Learning Research. 137, p. 136-147 12 p.Research output: Journal contributions › Conference article in journal › Research › peer-review
- 2019
- Published
Frame-based Optimal Design
Mair, S., Rudolph, Y., Closius, V. & Brefeld, U., 23.01.2019, Machine learning and knowledge discovery in databases: European Conference, ECML PKDD 2018, Dublin, Ireland, September 10-14, 2018 : proceedings. Berlingerio, M., Bonchi, F., Gärtner, T., Hurley, N. & Ifrim, G. (eds.). Cham: Springer Nature, Vol. 2. p. 447-463 17 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 11052 LNAI).Research output: Contributions to collected editions/works › Article in conference proceedings › Research › peer-review