MNC: Structure-Exploiting Sparsity Estimation for Matrix Expressions. - Johanna Sommer; Matthias Boehm 001; Alexandre V. Evfimievski; Berthold Reinwald; Peter J. Haas (SIGMOD Conference, 2019)

Learning to Tune XGBoost with XGBoost. - Johanna Sommer; Dimitrios Sarigiannis; Thomas P. Parnell (CoRR, 2019)

Neural Flows: Efficient Alternative to Neural ODEs. - Marin Bilos; Johanna Sommer; Syama Sundar Rangapuram; Tim Januschowski; Stephan Günnemann (NeurIPS, 2021)

Generalization of Neural Combinatorial Solvers Through the Lens of Adversarial Robustness. - Simon Geisler; Johanna Sommer; Jan Schuchardt; Aleksandar Bojchevski; Stephan Günnemann (ICLR, 2022)

MAGNet: Motif-Agnostic Generation of Molecules from Shapes. - Leon Hetzel; Johanna Sommer; Bastian Rieck; Fabian J. Theis; Stephan Günnemann (CoRR, 2023)

The power of motifs as inductive bias for learning molecular distributions. - Johanna Sommer; Leon Hetzel; David Lüdke; Fabian J. Theis; Stephan Günnemann (CoRR, 2023)

Expressivity and Generalization: Fragment-Biases for Molecular GNNs. - Tom Wollschläger; Niklas Kemper; Leon Hetzel; Johanna Sommer; Stephan Günnemann (ICML, 2024)

Unified Guidance for Geometry-Conditioned Molecular Generation. - Sirine Ayadi; Leon Hetzel; Johanna Sommer; Fabian J. Theis; Stephan Günnemann (NeurIPS, 2024)

OneProt: Towards Multi-Modal Protein Foundation Models. - Klemens Flöge; Srisruthi Udayakumar; Johanna Sommer; Marie Piraud; Stefan Kesselheim; Vincent Fortuin; Stephan Günnemann; Karel J. van der Weg; Holger Gohlke; Alina Bazarova; Erinc Merdivan (CoRR, 2024)

MAGNet: Motif-Agnostic Generation of Molecules from Scaffolds. - Leon Hetzel; Johanna Sommer; Bastian Rieck; Fabian J. Theis; Stephan Günnemann (ICLR, 2025)

Lift Your Molecules: Molecular Graph Generation in Latent Euclidean Space. - Mohamed Amine Ketata; Nicholas Gao; Johanna Sommer; Tom Wollschläger; Stephan Günnemann (ICLR, 2025)