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Since the latent space contains semantically meaningful directions and can be explained, we propose a pipeline to fully resolve the representation of the latent space. It consists of a Dirichlet encoder, conditional deterministic diffusion, a group-swap and a latent traversal module. ...
We aimed to identify intrinsic cliques of genes whose cell-type-specific expression robustly covaried with AD diagnosis across the cells in that measured brain tissue population. For that purpose, we brought to bear the class of supervised latent-factor models, which is under-represented in single...
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. ...
Single-cell analysis across multiple samples and conditions requires quantitative modeling of the interplay between the continuum of cell states and the technical and biological sources of sample-to-sample variability. We introduce GEDI, a generative mod
A number of limitations deserve consideration in interpreting the present findings. First, we note that even with the large sample size of the Grasby et al. [17,18] GWAS, there were many models that fit approximately as well as our final model in terms of the number of GIBNs and the ...
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...
His current research interests focus primarily on adoption and diffusion of emerging ICTs, e-commerce, m-commerce, digital and social media marketing and the role of artificial intelligence on the consumer decision-making and behaviour. He has published more than 300 papers in a range of lead- ...
While the model reduces to a non-diffusion one when ϕ=0, for all other values of ϕ, temporal sequences play a major role in the Kalman filter. This is never the case for the Bayesian learner model. Model fitting and comparisons Due to the reversal in performance levels between the ...
We developed a quantitative analysis method that manages multiple time scales from seconds to days and that rapidly fits many models of promoter dynamics. We found that RNA polymerases enter a long-lived pause at latent HIV-1 promoters (>20 minutes), thereby effectively limiting viral ...