Transformers are a neural network (NN) architecture, or model, that excels at processing sequential data by weighing the ...

Understanding how the brain learns and applies rules is the key to unraveling the neural basis of flexible behavior. A new ...

Cisco has been making good on its 2024 promise to place its bets on AI to the tune of $1 billion. One way the tech giant has been doing that is by investing heavily in AI startups that are new on the ...

Abstract: Electroencephalography (EEG) is a vital non-invasive technique used in neuroscience research and clinical diagnosis. However, EEG data have a complex non-Euclidean structure and are often ...

This repository contains a Monte-Carlo solver to train neural-network variational wavefunction to solve continuous-space Fermi systems [M Geier, K Nazaryan, T Zaklama, L Fu, Phys. Rev. B 112, 045119 ...

Neural networks first treat sentences like puzzles solved by word order, but once they read enough, a tipping point sends them diving into word meaning instead—an abrupt “phase transition” reminiscent ...

Increasingly, AI models are able make short-term weather forecasts with surprising accuracy. But neural networks only predict based on patterns from the past—what happens when the weather does ...

Abstract: Training neural networks (NNs) to behave as model predictive control (MPC) algorithms is an effective way to implement them in constrained embedded devices. By collecting large amounts of ...

Transport systems are unravelling in Spain and Portugal following massive power cuts across the Iberian peninsula. The electricity supply in both countries appears to have shut down at around 12.30pm ...

Modern AI excels at pattern recognition but suffers when faced with logical reasoning tasks. What happens when we ask a neural network to solve a Sudoku puzzle from an image, verify a mathematical ...