Schuchardt, Jan

12 publications

TMLR 2026 Amplified Patch-Level Differential Privacy for Free via Random Cropping Kaan Durmaz, Jan Schuchardt, Sebastian Schmidt, Stephan Günnemann

ICLRW 2025 Fast Proxies for LLM Robustness Evaluation Tim Beyer, Jan Schuchardt, Leo Schwinn, Stephan Günnemann

ICML 2025 Privacy Amplification by Structured Subsampling for Deep Differentially Private Time Series Forecasting Jan Schuchardt, Mina Dalirrooyfard, Jed Guzelkabaagac, Anderson Schneider, Yuriy Nevmyvaka, Stephan Günnemann

NeurIPS 2024 Unified Mechanism-Specific Amplification by Subsampling and Group Privacy Amplification Jan Schuchardt, Mihail Stoian, Arthur Kosmala, Stephan Günnemann

NeurIPS 2023 Hierarchical Randomized Smoothing Yan Scholten, Jan Schuchardt, Aleksandar Bojchevski, Stephan Günnemann

ICLR 2023 Localized Randomized Smoothing for Collective Robustness Certification Jan Schuchardt, Tom Wollschläger, Aleksandar Bojchevski, Stephan Günnemann

NeurIPS 2023 Provable Adversarial Robustness for Group Equivariant Tasks: Graphs, Point Clouds, Molecules, and More Jan Schuchardt, Yan Scholten, Stephan Günnemann

ICLR 2022 Generalization of Neural Combinatorial Solvers Through the Lens of Adversarial Robustness Simon Geisler, Johanna Sommer, Jan Schuchardt, Aleksandar Bojchevski, Stephan Günnemann

NeurIPS 2022 Invariance-Aware Randomized Smoothing Certificates Jan Schuchardt, Stephan Günnemann

NeurIPS 2022 Randomized Message-Interception Smoothing: Gray-Box Certificates for Graph Neural Networks Yan Scholten, Jan Schuchardt, Simon Geisler, Aleksandar Bojchevski, Stephan Günnemann

NeurIPSW 2022 Training Differentially Private Graph Neural Networks with Random Walk Sampling Morgane Ayle, Jan Schuchardt, Lukas Gosch, Daniel Zügner, Stephan Günnemann

ICLR 2021 Collective Robustness Certificates: Exploiting Interdependence in Graph Neural Networks Jan Schuchardt, Aleksandar Bojchevski, Johannes Gasteiger, Stephan Günnemann