Abstract: We present a general Bernoulli Gaussian scale mixture based approach for modeling priors that can represent ... Our method relies on intra-snapshot messages that update the signal vector for ...

Who we are? We are a just random people that loves games, gauss guns, crossplatform apps and so on.

The following is a summary of “Utilizing machine learning algorithms for predicting Anxiety-Depression Comorbidity Syndrome ...

Abstract: Recent work on dictionary learning with set-atoms has shown benefits in anomaly detection. Instead of viewing an atom as a single vector, these methods allow building sparse representations ...

SuperSplat is a free and open source tool for inspecting, editing, optimizing and publishing 3D Gaussian Splats. It is built on web technologies and runs in the browser, so there's nothing to download ...

These inferences are necessarily uncertain. Here, we illustrate how the Hierarchical Gaussian Filter (HGF) offers a principled and generic way to deal with the several forms that uncertainty in ...

A research group has developed an improved workflow for constructing machine learning (ML) models in oligonucleotide ...

An effective HIV-1 vaccine must therefore elicit antibodies that can neutralize many variants of the virus. While broadly neutralizing antibodies (bnAbs) have been isolated from HIV-1 infected ...

Alternative splicing (AS) of pre-mRNA plays a crucial role in tissue-specific gene regulation, with disease implications due to splicing defects. Predicting and manipulating AS can therefore uncover ...