Bernd Prach
5 Publications
2025 | Published | Thesis | IST-REx-ID: 19759 |

Prach B. Robust image classification with 1-Lipschitz networks. 2025. doi:10.15479/10.15479/at-ista-19759
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2024 | Published | Conference Paper | IST-REx-ID: 17426 |

Prach B, Brau F, Buttazzo G, Lampert C. 1-Lipschitz layers compared: Memory, speed, and certifiable robustness. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. Computer Vision Foundation; 2024:24574-24583. doi:10.1109/CVPR52733.2024.02320
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2024 | Draft | Preprint | IST-REx-ID: 18874 |

Prach B, Lampert C. Intriguing properties of robust classification. arXiv. doi:10.48550/arXiv.2412.04245
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2023 | Draft | Preprint | IST-REx-ID: 15039 |

Prach B, Lampert C. 1-Lipschitz neural networks are more expressive with N-activations. arXiv. doi:10.48550/ARXIV.2311.06103
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2022 | Published | Conference Paper | IST-REx-ID: 11839 |

Prach B, Lampert C. Almost-orthogonal layers for efficient general-purpose Lipschitz networks. In: Computer Vision – ECCV 2022. Vol 13681. Springer Nature; 2022:350-365. doi:10.1007/978-3-031-19803-8_21
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Grants
5 Publications
2025 | Published | Thesis | IST-REx-ID: 19759 |

Prach B. Robust image classification with 1-Lipschitz networks. 2025. doi:10.15479/10.15479/at-ista-19759
[Published Version]
View
| Files available
| DOI
2024 | Published | Conference Paper | IST-REx-ID: 17426 |

Prach B, Brau F, Buttazzo G, Lampert C. 1-Lipschitz layers compared: Memory, speed, and certifiable robustness. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. Computer Vision Foundation; 2024:24574-24583. doi:10.1109/CVPR52733.2024.02320
[Preprint]
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| Files available
| DOI
| Download Preprint (ext.)
| arXiv
2024 | Draft | Preprint | IST-REx-ID: 18874 |

Prach B, Lampert C. Intriguing properties of robust classification. arXiv. doi:10.48550/arXiv.2412.04245
[Preprint]
View
| Files available
| DOI
| Download Preprint (ext.)
| arXiv
2023 | Draft | Preprint | IST-REx-ID: 15039 |

Prach B, Lampert C. 1-Lipschitz neural networks are more expressive with N-activations. arXiv. doi:10.48550/ARXIV.2311.06103
[Preprint]
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| Files available
| DOI
| Download Preprint (ext.)
| arXiv
2022 | Published | Conference Paper | IST-REx-ID: 11839 |

Prach B, Lampert C. Almost-orthogonal layers for efficient general-purpose Lipschitz networks. In: Computer Vision – ECCV 2022. Vol 13681. Springer Nature; 2022:350-365. doi:10.1007/978-3-031-19803-8_21
[Preprint]
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| Files available
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| Download Preprint (ext.)
| arXiv