reference. We then compute the MARE and summarize results Table2. As explained in Figure2, we also report the MARE computed while excluding outlier samples where error exceeds the 90th percentile. In both cases, LDM3D-pano achieves lower MARE than the baseline panoramic depth estimation model. ...
In each sample, the gene expression vector of each archetype is determined by the sample-level variables (plus an additional variance that is not explained by sample characteristics), resulting in a ground-truth DE vector for each archetype and, by extension, any given cell state. Finally, ...
The PLS model tuning and ensuing classification performance depend on selecting an appropriate number of latent components, as supported by our data at hand. As each subsequently extracted latent component captures a complementary pattern in the transcriptome profiles, not already explained by a previous...
The PLS model tuning and ensuing classification performance depend on selecting an appropriate number of latent components, as supported by our data at hand. As each subsequently extracted latent component captures a complementary pattern in the transcriptome profiles, not already explained by a previous...
the same time equipping diffusion models with the low-dimensional VAE inferred latent code which can be used for downstream tasks like controllable synthesis and image attribute manipulation. In short, DiffuseVAE presents a generative model which combines the benefits of both VAEs and Diffusion models...
We developed a numerical diffusion model that accommodated temperature dependent kinetics and explained the observed deviations by incorporating de-passivation and dissolution phenomena. Numerical fitting of the model to the experiments provided optimized mobility parameters that agree with those reported for ...
(2023, Fig. 3a) showed using simulations that a neutral, parametric demographic model fitted to these data also explained the frequencies of mutation in counts n1≤104. Polymorphic sites with small mutation counts comprise the bulk of variation in humans. They represent a rich source of ...
explained by the following example, “A style vector that edits the person’s lip makeup can contain style channels that determine the boundaries of the lips in the edited generated image.” The authors who discovered the Style Space describe a method for discovering a large collection of style...
Altogether, these data demonstrate that HeLa cells latently infected with HIV-1 display rare bursts of viral transcription, which are best explained by stochastic pausing. Fig. 8: Bursting of the HIV-1 promoter in latently infected HeLa cells. A Schematic of the HIV-1 reporter construct used ...
model to generate realistic histopathology images, which can be explained by the lack of digital pathology images in LAION, the large-scale dataset used for training vanilla SD [40]. Further supporting this, there is also a visually obvious increase in image quality after fine-tuning with in-...