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Jan Schuchardt
Titlu
Citat de
Citat de
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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
462022
Collective Robustness Certificates: Exploiting Interdependence in Graph Neural Networks
J Schuchardt, A Bojchevski, J Gasteiger, S Günnemann
International Conference on Learning Representations (ICLR), 2021
392021
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
232022
Learning to Evolve
J Schuchardt, V Golkov, D Cremers
arXiv preprint arXiv:1905.03389, 2019
112019
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
102022
Localized Randomized Smoothing for Collective Robustness Certification
J Schuchardt, T Wollschläger, A Bojchevski, S Günnemann
International Conference on Learning Representations (ICLR), 2023
92023
Hierarchical Randomized Smoothing
Y Scholten, J Schuchardt, A Bojchevski, S Günnemann
Advances in Neural Information Processing Systems (NeurIPS), 2023
72023
Invariance-Aware Randomized Smoothing Certificates
J Schuchardt, S Günnemann
Advances in Neural Information Processing Systems (NeurIPS), 2022
72022
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
42023
Unified Mechanism-Specific Amplification by Subsampling and Group Privacy Amplification
J Schuchardt, M Stoian, A Kosmala, S Günnemann
Advances in Neural Information Processing Systems (NeurIPS), 2024
22024
Fast Proxies for LLM Robustness Evaluation
T Beyer, J Schuchardt, L Schwinn, S Günnemann
arXiv preprint arXiv:2502.10487, 2025
2025
Privacy Amplification by Structured Subsampling for Deep Differentially Private Time Series Forecasting
J Schuchardt, M Dalirrooyfard, J Guzelkabaagac, A Schneider, ...
arXiv preprint arXiv:2502.02410, 2025
2025
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