This valuable study links psychological theories of chunking with a physiological implementation based on short-term synaptic plasticity and synaptic augmentation. The theoretical derivation for ...

The representation of individual memories in a recurrent neural network can be efficiently differentiated using chaotic recurrent dynamics.

GenAI isn’t magic — it’s transformers using attention to understand context at scale. Knowing how they work will help CIOs ...

Neuroscientists have been trying to understand how the brain processes visual information for over a century. The development ...

Artificial intelligence is quietly reshaping how crops are bred, and the biggest gains may come not in corn or wheat but in ...

In this video, we will understand Backpropagation in RNN. It is also called Backpropagation through time, as here we are ...

ABSTRACT: Context and Justification: As financial services undergo accelerated digitalization, the expansion of electronic transactions within digital wallets increases vulnerabilities to fraud, ...

Abstract: Several studies have analyzed traffic patterns using Vehicle Detector (VD) and Global Positioning System (GPS) data. VD records the speed of vehicles passing through detectors, GPS data ...

Members use social platforms to push vulnerable teens into harming themselves. In striking and chilling terms, several career Justice Department officials on Thursday offered dire warnings about the ...

Abstract: Unlike traditional feedforward neural networks, recurrent neural networks (RNNs) possess a recurrent connection that allows them to retain past information. This internal memory enables RNNs ...