Background Comparative evidence on the diagnostic yield of endobronchial ultrasound (EBUS)-guided sampling techniques for ...

An international analysis combining brain imaging data from multiple independent studies has identified a common pattern in ...

Imagine a scenario where a team of doctors faces a perplexing medical puzzle. A patient shows a range of symptoms, each pointing to multiple possible diseases. How can they navigate this diagnostic ...

Abstract: The accuracy of target threat estimation has a great impact on command decision-making. The Bayesian network, as an effective way to deal with the problem of uncertainty, can be used to ...

If you want to advance your career, you’ll need to build a strong network. The statistics make the case: 54% of people report getting their job through a connection, according to a 2025 survey by ...

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, ...

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 ...

Abstract: Bayesian network structure learning is one of the current research hotspots in fields such as statistics and machine learning. Although it has great potential and application prospects, when ...

Implementation of BANSAC, a new guided sampling process for RANSAC. Previous methods either assume no prior information about the inlier/outlier classification of data points or use some previously ...

Understanding the interplay between network architecture, dataset statistics, and learning algorithms is a key challenge in deep learning. We overcome this challenge analytically for zero-noise ...