Simon Damm, M.Sc.

PhD Student

MC 5.126
simon.damm@rub.de

ELLIS PhD Student

Research Interests

  • Probabilistic generative modeling
  • Out-of-distribution & anomaly detection
  • Machine/Deep learning for spatiotemporal data

Publications

2025

Simon Damm, Asja Fischer, Alexander May, Soundes Marzougui, Leander Schwarz, Henning Seidler, Jean-Pierre Seifert, Jonas Thietke, Vincent Quentin Ulitzsch

Solving Concealed ILWE and its Application for Breaking Masked Dilithium Proceedings Article

In: Advances in Cryptology (ASIACRYPT 25), 2025.

Links

Simon Damm, Nicolai Kraus, Alexander May, Julian Nowakowski, Jonas Thietke

One Bit to Rule Them All - Imperfect Randomness Harms Lattice Signatures Proceedings Article

In: Public Key Cryptography (PKC '25), 2025.

Links

Simon Damm, Mike Laszkiewicz, Johannes Lederer, Asja Fischer

AnomalyDINO: Boosting Patch-based Few-shot Anomaly Detection with DINOv2 Proceedings Article

In: IEEE/CVF Winter Conference on Applications of Computer Vision (WACV), 2025.

Links

Sina Däubener, Simon Damm, Asja Fischer

ELBO, Regularized Maximum Likelihood, and Their Common One-Sample Approximation for Training Stochastic Neural Networks Proceedings Article

In: Conference on Uncertainty in Artificial Intelligence (UAI), 2025.

Links

2024

Jonas Ricker, Simon Damm, Thorsten Holz, Asja Fischer

Towards the Detection of Diffusion Model Deepfakes Proceedings Article

In: International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP), 2024.

Links

Dmytro Velychko, Simon Damm, Asja Fischer, Jörg Lücke

Learning sparse codes with entropy-based ELBOs Proceedings Article

In: International Conference on Artificial Intelligence and Statistics (AISTATS), 2024.

Links

2023

Simon Damm, Dennis Forster, Dmytro Velychko, Zhenwen Dai, Asja Fischer, Jörg Lücke

The ELBO of variational autoencoders converges to a sum of entropies Proceedings Article

In: International Conference on Artificial Intelligence and Statistics (AISTATS), 2023.

Links