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Lukas Gosch
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引用次数
引用次数
年份
DeepNOG: fast and accurate protein orthologous group assignment
R Feldbauer, L Gosch, L Lüftinger, P Hyden, A Flexer, T Rattei
Bioinformatics 36 (22-23), 5304-5312, 2020
212020
Revisiting Robustness in Graph Machine Learning
L Gosch, D Sturm, S Geisler, S Günnemann
International Conference on Learning Representations (ICLR) 2023. Also TSRML …, 2023
192023
Adversarial Training for Graph Neural Networks: Pitfalls, Solutions, and New Directions
L Gosch, S Geisler, D Sturm, B Charpentier, D Zügner, S Günnemann
Thirty-seventh Conference on Neural Information Processing Systems (NeurIPS), 2023
162023
Training Differentially Private Graph Neural Networks with Random Walk Sampling
M Ayle, J Schuchardt, L Gosch, D Zügner, S Günnemann
Workshop on Trustworthy and Socially Responsible Machine Learning, NeurIPS 2022, 2022
52022
Assessing robustness via score-based adversarial image generation
M Kollovieh, L Gosch, Y Scholten, M Lienen, S Günnemann
arXiv preprint arXiv:2310.04285, 2023
42023
Expressivity of graph neural networks through the lens of adversarial robustness
F Campi, L Gosch, T Wollschläger, Y Scholten, S Günnemann
arXiv preprint arXiv:2308.08173, 2023
22023
Relaxing Graph Transformers for Adversarial Attacks
P Foth, L Gosch, S Geisler, L Schwinn, S Günnemann
arXiv preprint arXiv:2407.11764, 2024
2024
Provable Robustness of (Graph) Neural Networks Against Data Poisoning and Backdoor Attacks
L Gosch, M Sabanayagam, D Ghoshdastidar, S Günnemann
arXiv preprint arXiv:2407.10867, 2024
2024
On Modelling and Solving Green Collaborative Tactical Transportation Planning
L Gosch, M Prandtstetter, K Dörner
International Physical Internet Conference IPIC 2021, 2021
2021
Shortcomings and New Perspectives on Mutual Information for Representation Learning
L Gosch
2020
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