1 citations · 1 across the 4 of their papers we have counts for
4 papers
Beyond Sample Copying: Structural Memorization in Diffusion Models
Tim Kaiser, Markus Kollmann
Diffusion models generalize well in practice. Paradoxically, an optimal diffusion model fully memorizes the training data and therefore fails to generalize, raising the question of…
Guiding a diffusion model using sliding windows
Nikolas Adaloglou, Tim Kaiser, Damir Iagudin +1
Guidance is a widely used technique for diffusion models to enhance sample quality. Technically, guidance is realised by using an auxiliary model that generalises more broadly than…
Rethinking cluster-conditioned diffusion models for label-free image synthesis
Nikolas Adaloglou, Tim Kaiser, Felix Michels +1
Diffusion-based image generation models can enhance image quality when conditioned on ground truth labels. Here, we conduct a comprehensive experimental study on image-level condit…
Adapting Contrastive Language-Image Pretrained (CLIP) Models for Out-of-Distribution Detection
Nikolas Adaloglou, Felix Michels, Tim Kaiser +1
We present a comprehensive experimental study on pretrained feature extractors for visual out-of-distribution (OOD) detection, focusing on adapting contrastive language-image pretr…