Calculations show that injecting randomness into a quantum neural network could help it determine properties of quantum ...

Ixana's Wi-R network could help smart glasses stream more reliably to other connected wearables. After seeing a few demos at ...

Researchers have developed a hybrid CFD-neural network model for predicting TAIs in hydrogen-fueled turbines, improving ...

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 ...

Abstract: One of the most popular recent areas of machine learning predicates the use of neural networks (NNs) augmented by information about the underlying process in the form of partial differential ...

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, ...

This repository is an implementation of our paper "Contrastive Prior Enhances the Performance of Bayesian Neural Network-based Molecular Property Prediction" in PyTorch. In this work, we propose a ...

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 ...

1 Department of Mathematical Sciences, Sol Plaatje University, Kimberley, South Africa 2 Department of Computer Science and Information Technology, Sol Plaatje University, Kimberley, South Africa Deep ...