Publications

Visonà, G.; Duroux, D.; Miranda, L.; Sükei, E.; Li, Y.; Borgwardt, K.; Oliver, C.: Multimodal learning in clinical proteomics: enhancing antimicrobial resistance prediction models with chemical information. Bioinformatics, btad717 (2023)

Moor, M.; Bennett, N.; Plečko, D.; Horn, M.; Rieck, B.; Meinshausen, N.; Bühlmann, P.; Borgwardt, K.: Predicting sepsis using deep learning across international sites: a retrospective development and validation study. eClinicalMedicine 62, 102124 (2023)

Pellizzoni, P.; Muzio, G.; Borgwardt, K.: Higher-order genetic interaction discovery with network-based biological priors. Bioinformatics 39 (Supplement_1), pp. 523 - 533 (2023)

Muzio, G.; O’Bray, L.; Meng-Papaxanthos, L.; Klatt, J.; Borgwardt, K.: networkGWAS: A network-based approach to discover genetic associations. Bioinformatics 39 (6), btad370 (2023)

Togninalli, M.; Wang, X.; Kucera, T.; Shrestha, S.; Juliana, P.; Mondal, S.; Pinto, F.; Govindan, V.; Crespo-Herrera, L.; Huerta-Espino, J. et al.; Singh, R. P.; Borgwardt, K.; Poland, J.: Multi-modal deep learning improves grain yield prediction in wheat breeding by fusing genomics and phenomics. Bioinformatics 39 (6), btad336 (2023)

Chen, D.; Fan, B.; Oliver, C.; Borgwardt, K.: Unsupervised Manifold Alignment with Joint Multidimensional Scaling. Eleventh International Conference on Learning Representations (ICLR 2023) (2023)

Chen, D.; Pellizzoni , P.; Borgwardt, K.: Fisher Information Embedding for Node and Graph Learning. Proceedings of the 40th International Conference on Machine Learning (ICML 2023), PMLR 202 (2023)

Pellizzoni, P.; Borgwardt, K.: FASM and FAST-YB: Significant Pattern Mining with False Discovery Rate Control. 2023 IEEE International Conference on Data Mining (ICDM), pp. 1265 - 1270 (2023)