Abstract: Predictive maintenance is essential for ensuring the reliability and efficiency of wind energy systems. Traditional deep learning models for sensor fault detection rely solely on data-driven ...

Welcome to the inference code for the paper "Protein Sequence Modelling with Bayesian Flow Networks". With this code, you can sample from our trained models ProtBFN, for general proteins, and AbBFN, ...

Gut bacteria are known to be a key factor in many health-related concerns. However, the number and variety of them is vast, as are the ways in which they interact with the body’s chemistry and each ...

Neural processing unts (NPUs) are the latest chips you might find in smartphones and laptops — but what are they ard why are they so important? When you purchase through links on our site, we may earn ...

The Evidence Lower Bound (ELBO) is a key objective for training generative models like Variational Autoencoders (VAEs). It parallels neuroscience, aligning with the Free Energy Principle (FEP) for ...

Traditionally, the ampacity of an overhead transmission line (OHTL) is a static value obtained based on adverse weather conditions, which constrains the transmission capacity. With the continuous ...

Abstract: Causal inference is an important function of the nervous system. To explore causal inference, Bayesian inference performs as the possible framework, mapping neural implementation onto ...

The sinking of tech billionaire Mike Lynch’s yacht in a freak storm off the Sicilian coast last week certainly has to rank among the most bizarre fatal celebrity accidents in years. There was the ...