Humans have the remarkable ability to remember the same person or object in completely different situations. We can easily ...

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Neuroscientists have been trying to understand how the brain processes visual information for over a century. The development of computational models inspired by the brain's layered organization, also ...

Ixana's Wi-R network could be a way to help smart glasses stream more reliably to a wide range of connected wearables, and after seeing a few demos, I'm eager to learn more.

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

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 ...

The study, titled Reinforcement Learning for Monetary Policy Under Macroeconomic Uncertainty: Analyzing Tabular and Function ...

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 ...