Lukas Gosch

According to our database, Lukas Gosch authored at least 13 papers between 2021 and 2026.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2026

Exact Certification of Neural Networks and Partition Aggregation Ensembles against Label Poisoning.

Ajinkya Mohgaonkar, Lukas Gosch, Mahalakshmi Sabanayagam, Debarghya Ghoshdastidar, Stephan Günnemann

CoRR, April, 2026

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

Adversarial Robustness of Graph Transformers.

Philipp Foth, Lukas Gosch, Simon Geisler, Leo Schwinn, Stephan Günnemann

Trans. Mach. Learn. Res., 2025

Exact Certification of (Graph) Neural Networks Against Label Poisoning.

Mahalakshmi Sabanayagam, Lukas Gosch, Stephan Günnemann, Debarghya Ghoshdastidar

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

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

Relaxing Graph Transformers for Adversarial Attacks.

Philipp Foth, Lukas Gosch, Simon Geisler, Leo Schwinn, Stephan Günnemann

CoRR, 2024

2023

Assessing Robustness via Score-Based Adversarial Image Generation.

Marcel Kollovieh, Lukas Gosch, Yan Scholten, Marten Lienen, 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

Adversarial Training for Graph Neural Networks.

Lukas Gosch, Simon Geisler, Daniel Sturm, Bertrand Charpentier, Daniel Zügner, Stephan Günnemann

CoRR, 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: Pitfalls, Solutions, and New Directions.

Lukas Gosch, Simon Geisler, Daniel Sturm, Bertrand Charpentier, Daniel Zügner, Stephan Günnemann

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Revisiting Robustness in Graph Machine Learning.

Lukas Gosch, Daniel Sturm, Simon Geisler, Stephan Günnemann

Proceedings of the Eleventh International Conference on Learning Representations, 2023

2021

DeepNOG: fast and accurate protein orthologous group assignment.

Roman Feldbauer, Lukas Gosch, Lukas Lüftinger, Patrick Hyden, Arthur Flexer, Thomas Rattei

Bioinform., 2021