| 2025 | ICLR | How many samples are needed to train a deep neural network? | Pegah Golestaneh, Mahsa Taheri, Johannes Lederer |
| 2025 | WACV | AnomalyDINO: Boosting Patch-based Few-Shot Anomaly Detection with DINOv2. | Simon Damm, Mike Laszkiewicz, Johannes Lederer, Asja Fischer |
| 2024 | ICML | Single-Model Attribution of Generative Models Through Final-Layer Inversion. | Mike Laszkiewicz, Jonas Ricker, Johannes Lederer, Asja Fischer |
| 2022 | ICML | Marginal Tail-Adaptive Normalizing Flows. | Mike Laszkiewicz, Johannes Lederer, Asja Fischer |
| 2021 | AISTATS | Thresholded Adaptive Validation: Tuning the Graphical Lasso for Graph Recovery. | Mike Laszkiewicz, Asja Fischer, Johannes Lederer |
| 2021 | AISTATS | False Discovery Rates in Biological Networks. | Lu Yu, Tobias Kaufmann, Johannes Lederer |
| 2015 | AAAI | Compute Less to Get More: Using ORC to Improve Sparse Filtering. | Johannes Lederer, Sergio Guadarrama |
| 2015 | AAAI | Don't Fall for Tuning Parameters: Tuning-Free Variable Selection in High Dimensions With the TREX. | Johannes Lederer, Christian L. Mller |