21 citations · 21 across the 6 of their papers we have counts for
6 papers
The Spacetime of Diffusion Models: An Information Geometry Perspective
Rafał Karczewski, Markus Heinonen, Alison Pouplin +2
We present a novel geometric perspective on the latent space of diffusion models. We first show that the standard pullback approach, utilizing the deterministic probability flow OD…
Devil is in the Details: Density Guidance for Detail-Aware Generation with Flow Models
Rafał Karczewski, Markus Heinonen, Vikas Garg
Diffusion models have emerged as a powerful class of generative models, capable of producing high-quality images by mapping noise to a data distribution. However, recent findings s…
Diffusion Models as Cartoonists: The Curious Case of High Density Regions
Rafał Karczewski, Markus Heinonen, Vikas Garg
We investigate what kind of images lie in the high-density regions of diffusion models. We introduce a theoretical mode-tracking process capable of pinpointing the exact mode of th…
What Ails Generative Structure-based Drug Design: Expressivity is Too Little or Too Much?
Rafał Karczewski, Samuel Kaski, Markus Heinonen +1
Several generative models with elaborate training and sampling procedures have been proposed to accelerate structure-based drug design (SBDD); however, their empirical performance…
Inhibited Softmax for Uncertainty Estimation in Neural Networks
Marcin Możejko, Mateusz Susik, Rafał Karczewski
We present a new method for uncertainty estimation and out-of-distribution detection in neural networks with softmax output. We extend softmax layer with an additional constant inp…
Linearity of regression for weak records, revisited
Rafał Karczewski, Jacek Wesołowski
Since many years characterization of distribution by linearity of regression of non-adjacent weak records E(W_{i+s}|W_i) = β_1 W_i+β_0 for discrete observations has been known to b…