Publications

Please find our computer science publications before 2001 at DBLP and our life science and application-related publications before 2001 at PubMed.


2024

King, R. D., Scassa, T., Kramer, S., and Kitano, H. (2024). Stockholm declaration on AI ethics: why others should sign. Nature, 626(8000), 716-716. DOI
Derstroff, C., Brugger, J., Blüml, J., et al. (2024). Amplifying Exploration in Monte-Carlo Tree Search by Focusing on the Unknown. CoRR, abs/2402.08511. DOI Author/Publisher URL

2023

Lang, F., Sorn, P., Schrörs, B., et al. (2023). Multiple instance learning to predict immune checkpoint blockade efficacy using neoantigen candidates. iScience, 26(11), 108014. DOI Author/Publisher URL
Vexler, J., Kramer, S. (2023). Classifying Aircraft Categories from Magnetometry Data Using a Hypotheses-Based Multi-Task Framework. In Frontiers in Artificial Intelligence and Applications. IOS Press. DOI
Vexler, J., Kramer, S. (2023, June 28). Identifying Aircraft Motions and Patterns from Magnetometry Data Using a Knowledge-Based Multi-Fusion Approach. 2023 26th International Conference on Information Fusion (FUSION). Published. 2023 26th International Conference on Information Fusion (FUSION). DOI
Lerner, R., Baker, D., Schwitter, C., et al. (2023). Four-dimensional trapped ion mobility spectrometry lipidomics for high throughput clinical profiling of human blood samples. Nature Communications, 14(1). DOI
Bammert, L.-M., Kramer, S., Cerrato, M., Althaus, E. (2023). Privacy-Preserving Learning of Random Forests Without Revealing the Trees. In A. Bifet, A. C. Lorena, R. P. Ribeiro, et al. (eds.), DS (Vols 14276, pp. 372-386). Springer. Author/Publisher URL
Cerrato, M., Köppel, M., Esposito, R., Kramer, S. (2023). Invariant Representations with Stochastically Quantized Neural Networks. In B. Williams, Y. Chen, J. Neville (eds.), Thirty-Seventh AAAI Conference on Artificial Intelligence, AAAI 2023, Thirty-Fifth Conference on Innovative Applications of Artificial Intelligence, IAAI 2023, Thirteenth Symposium on Educational Advances in Artificial Intelligence, EAAI 2023, Washington, DC, USA, February 7-14, 2023 (pp. 6962-6970). AAAI Press. DOI Author/Publisher URL
Derstroff, C., Cerrato, M., Brugger, J., et al. (2023). Peer Learning: Learning Complex Policies in Groups from Scratch via Action Recommendations. CoRR, abs/2312.09950. DOI Author/Publisher URL
Hauptmann, T., Kramer, S. (2023). A fair experimental comparison of neural network architectures for latent representations of multi-omics for drug response prediction. BMC BIOINFORMATICS, 24(1). DOI Author/Publisher URL
Hauptmann, T., Fellenz, S., Nathan, L., et al. (2023). Discriminative machine learning for maximal representative subsampling. SCIENTIFIC REPORTS, 13(1). DOI Author/Publisher URL
Kramer, S., Cerrato, M., Dzeroski, S., King, R. D. (2023). Automated Scientific Discovery: From Equation Discovery to Autonomous Discovery Systems. CoRR, abs/2305.02251. DOI Author/Publisher URL

2022

Pensel, L., Kramer, S. (2022). Neural RELAGGS. Author/Publisher URL
Hauptmann, T., Kramer, S. (2022). A Fair Experimental Comparison of Neural Network Architectures for Latent Representations of Multi-Omics for Drug Response Prediction. Author/Publisher URL
Cerrato, M., Coronel, A. V., Köppel, M., et al. (2022). Fair Interpretable Representation Learning with Correction Vectors. CoRR, abs/2202.03078. Author/Publisher URL
Cerrato, M., Köppel, M., Segner, A., Kramer, S. (2022). Fair Group-Shared Representations with Normalizing Flows. CoRR, abs/2201.06336. Author/Publisher URL
Cerrato, M., Köppel, M., Segner, A., Kramer, S. (2022). Fair Interpretable Learning via Correction Vectors. CoRR, abs/2201.06343. Author/Publisher URL
Garcon, A., Vexler, J., Budker, D., Kramer, S. (2022). Deep neural networks to recover unknown physical parameters from oscillating time series. PLOS ONE, 17(5). DOI Author/Publisher URL
Koeppel, M., Segner, A., Wagener, M., et al. (2022). Learning to rank Higgs boson candidates. SCIENTIFIC REPORTS, 12(1). DOI Author/Publisher URL
Siekiera, J., Köppel, M., Simpson, E., et al. (2022). Ranking Creative Language Characteristics in Small Data Scenarios. In M. M. Hedblom, A. A. Kantosalo, R. Confalonieri, et al. (eds.), Proceedings of the 13th International Conference on Computational Creativity, Bozen-Bolzano, Italy, June 27 - July 1, 2022 (pp. 136-140). Association for Computational Creativity (ACC). Author/Publisher URL