Folgen
Jan Schuchardt
Titel
Zitiert von
Zitiert von
Jahr
Generalization of Neural Combinatorial Solvers Through the Lens of Adversarial Robustness
S Geisler, J Sommer, J Schuchardt, A Bojchevski, S Günnemann
International Conference on Learning Representations (ICLR), 2022
332022
Collective Robustness Certificates: Exploiting Interdependence in Graph Neural Networks
J Schuchardt, A Bojchevski, J Gasteiger, S Günnemann
International Conference on Learning Representations (ICLR), 2021
302021
Randomized Message-Interception Smoothing: Gray-Box Certificates for Graph Neural Networks
Y Scholten, J Schuchardt, S Geisler, A Bojchevski, S Günnemann
Advances in Neural Information Processing Systems (NeurIPS), 2022
112022
Learning to Evolve
J Schuchardt, V Golkov, D Cremers
arXiv preprint arXiv:1905.03389, 2019
112019
Localized Randomized Smoothing for Collective Robustness Certification
J Schuchardt, T Wollschläger, A Bojchevski, S Günnemann
International Conference on Learning Representations (ICLR), 2023
52023
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
52022
Invariance-Aware Randomized Smoothing Certificates
J Schuchardt, S Günnemann
Advances in Neural Information Processing Systems (NeurIPS), 2022
42022
Provable Adversarial Robustness for Group Equivariant Tasks: Graphs, Point Clouds, Molecules, and More
J Schuchardt, Y Scholten, S Günnemann
Advances in Neural Information Processing Systems (NeurIPS), 2023
32023
Hierarchical Randomized Smoothing
Y Scholten, J Schuchardt, A Bojchevski, S Günnemann
Advances in Neural Information Processing Systems (NeurIPS), 2023
32023
Group Privacy Amplification and Unified Amplification by Subsampling for Rényi Differential Privacy
J Schuchardt, M Stoian, A Kosmala, S Günnemann
arXiv preprint arXiv:2403.04867, 2024
2024
Das System kann den Vorgang jetzt nicht ausführen. Versuchen Sie es später erneut.
Artikel 1–10