Fakultät für Informatik

Assoz. Prof. Dipl.-Inf. Dr. Nils Morten Kriege

Forschungsgruppe Data Mining and Machine Learning

Währinger Straße 29
1090 Wien
Raum : 6.38

T: +43-1-4277-79512

nils.kriege(at)univie.ac.at

Persönliche Homepage

u:cris-Portal

Lehrveranstaltungen

Publikationen

Spectral Basis Learning for Expressive Graph Neural Networks in Link Prediction. / Azizi, Niloofar; Kriege, Nils M.; Harvey, Nicholas et al.
in: Proceedings of the ... National Conference on Artificial Intelligence, Band 40, Nr. 24, 14.03.2026, S. 19640-19648.

Veröffentlichungen: Beitrag in Fachzeitschrift › Meeting Abstract/Conference Paper › Peer Reviewed

Weisfeiler and Leman Go Gambling: Why Expressive Lottery Tickets Win. / Kummer, Lorenz; Moustafa, Samir; Ehrlich, Anatol et al.
Proceedings of the 42nd International Conference on Machine Learning. Band 267 PMLR, 2025. S. 31991-32010 (Proceedings of Machine Learning Research (PMLR), Band 267).

Veröffentlichungen: Beitrag in Buch › Beitrag in Konferenzband › Peer Reviewed

Visualization and Analysis of the Loss Landscape in Graph Neural Networks. / Moustafa, Samir (Korresp. Autor*in); Kummer, Lorenz; Fetzel, Simon et al.
Artificial Neural Networks and Machine Learning. ICANN 2025 International Workshops and Special Sessions: 34th International Conference on Artificial Neural Networks, Kaunas, Lithuania, September 9–12, 2025, Proceedings, Part V. Springer Cham, 2025. S. 69-81 (Lecture Notes in Computer Science).

Veröffentlichungen: Beitrag in Buch › Beitrag in Konferenzband › Peer Reviewed

doi.org/10.1007/978-3-032-04552-2_9

Efficient Mixed Precision Quantization in Graph Neural Networks. / Moustafa, Samir ; Kriege, Nils M.; Gansterer, Wilfried (Korresp. Autor*in).
41st IEEE International Conference on Data Engineering. 2025. S. 4038-4052.

Veröffentlichungen: Beitrag in Buch › Beitrag in Konferenzband › Peer Reviewed

doi.org/10.1109/ICDE65448.2025.00301

On the Relationship Between Robustness and Expressivity of Graph Neural Networks. / Kummer, Lorenz; Gansterer, Wilfried ; Kriege, Nils Morten.
Proceedings of the 28th International Conference on Artificial Intelligence and Statistics. Band 258 PMLR, 2025. S. 1243-1251 (Proceedings of Machine Learning Research (PMLR)).

Veröffentlichungen: Beitrag in Buch › Beitrag in Konferenzband › Peer Reviewed

Crossfire: An Elastic Defense Framework for Graph Neural Networks Under Bit Flip Attacks. / Kummer, Lorenz; Moustafa, Samir ; Gansterer, Wilfried et al.
Proceedings of the 39th Annual AAAI Conference on Artificial Intelligence. AAAI, 2025. S. 17990-17998 (Proceedings of the ... National Conference on Artificial Intelligence; Nr. 17, Band 39).

Veröffentlichungen: Beitrag in Buch › Beitrag in Konferenzband › Peer Reviewed

doi.org/10.1609/aaai.v39i17.33979

Maximally Expressive GNNs for Outerplanar Graphs. / Bause, Franka; Jogl, Fabian; Indri, Patrick et al.
in: Transactions on Machine Learning Research (TMLR), 03.01.2025.

Veröffentlichungen: Beitrag in Fachzeitschrift › Artikel › Peer Reviewed

Chemical Similarity and Substructure Searches. / Kriege, Nils Morten ; Seidel, Thomas; Humbeck, Lina et al.
Encyclopedia of Bioinformatics and Computational Biology. Band 3 2. Aufl. Elsevier, 2025. S. 707-719.

Veröffentlichungen: Beitrag in Buch › Beitrag in Buch/Sammelband › Peer Reviewed

doi.org/10.1016/B978-0-323-95502-7.00048-8

sc-GRIP: a Graph Convolutional Approach to Infer Gene Interaction Polarity from Single-cell Data. / Atria, Carolina Elisabeth ; Cai, Yitao ; Weber, Pascal et al.
2025. Beitrag in International Conference on Data Mining, Washington DC, USA / Vereinigte Staaten.

Veröffentlichungen: Beitrag zu Konferenz › Paper › Peer Reviewed

Attacking Graph Neural Networks with Bit Flips: Weisfeiler and Leman Go Indifferent. / Kummer, Lorenz; Moustafa, Samir ; Schrittwieser, Sebastian et al.
Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining: KDD 2024. New York: Association for Computing Machinery (ACM), 2024. S. 1428-1439.

Veröffentlichungen: Beitrag in Buch › Beitrag in Konferenzband › Peer Reviewed

doi.org/10.1145/3637528.3671890

Projekte

StruDL: Structured Data Learning with General Similarities

Kriege, N. M. (Projektleiter*in), Gärtner, T. (Co-Projektleiter*in) & Flamm, C. (Co-Projektleiter*in)

1/05/23 → 31/10/27

Projekt: Forschungsförderung

Geometric deep leaning based recommender engine with implicit feedback data in e-commerce domain (GNN Recsys)

Kriege, N. M. (Projektleiter*in)

1/02/22 → 30/06/24

Projekt: Forschungskooperation

Algorithmic Data Science for Computational Drug Discovery

Kriege, N. M. (Projektleiter*in) & Gansterer, W. (Co-Projektleiter*in)

1/05/20 → 30/11/28

Projekt: Forschungsförderung

Vorträge

Sc-GRIP: a Graph Convolutional Approach to Infer Gene Interaction Polarity from Single-Cell Data

Cai, Y. (Keynote speaker), Atria, C. E. (Autor*in), Weber, P. (Autor*in), Beer, A. (Autor*in), Kriege, N. M. (Autor*in), Böhm, C. (Autor*in), Revilla Domingo, R. (Autor*in) & Plant, C. (Autor*in)

8 Feb. 2026

Aktivität: Vorträge › Vortrag › Science to Science