DeepNOG: fast and accurate protein orthologous group assignment. - Roman Feldbauer; Lukas Gosch; Lukas Lüftinger; Patrick Hyden; Arthur Flexer; Thomas Rattei (Bioinform., 2021)

Revisiting Robustness in Graph Machine Learning. - Lukas Gosch; Daniel Sturm 002; Simon Geisler; Stephan Günnemann (ICLR, 2023)

Adversarial Training for Graph Neural Networks: Pitfalls, Solutions, and New Directions. - Lukas Gosch; Simon Geisler; Daniel Sturm 002; Bertrand Charpentier; Daniel Zügner; Stephan Günnemann (NeurIPS, 2023)

Training Differentially Private Graph Neural Networks with Random Walk Sampling. - Morgane Ayle; Jan Schuchardt; Lukas Gosch; Daniel Zügner; Stephan Günnemann (CoRR, 2023)

Adversarial Training for Graph Neural Networks. - Lukas Gosch; Simon Geisler; Daniel Sturm 002; Bertrand Charpentier; Daniel Zügner; Stephan Günnemann (CoRR, 2023)

Expressivity of Graph Neural Networks Through the Lens of Adversarial Robustness. - Francesco Campi; Lukas Gosch; Tom Wollschläger; Yan Scholten; Stephan Günnemann (CoRR, 2023)

Assessing Robustness via Score-Based Adversarial Image Generation. - Marcel Kollovieh; Lukas Gosch; Yan Scholten; Marten Lienen; Stephan Günnemann (CoRR, 2023)

Relaxing Graph Transformers for Adversarial Attacks. - Philipp Foth; Lukas Gosch; Simon Geisler; Leo Schwinn; Stephan Günnemann (CoRR, 2024)

Assessing Robustness via Score-Based Adversarial Image Generation. - Marcel Kollovieh; Lukas Gosch; Marten Lienen; Yan Scholten; Leo Schwinn; Stephan Günnemann (Trans. Mach. Learn. Res., 2024)

Exact Certification of (Graph) Neural Networks Against Label Poisoning. - Mahalakshmi Sabanayagam; Lukas Gosch; Stephan Günnemann; Debarghya Ghoshdastidar (ICLR, 2025)

Provable Robustness of (Graph) Neural Networks Against Data Poisoning and Backdoor Attacks. - Lukas Gosch; Mahalakshmi Sabanayagam; Debarghya Ghoshdastidar; Stephan Günnemann (Trans. Mach. Learn. Res., 2025)