In recent years, more and more people suffer from voice-related diseases. Given the limitations of current pathological speech conversion methods, that is, a method can only convert a single kind of ...

Mechanistic modeling with low-rank recurrent networks uncovers the relationship between network connectivity, neural dynamics, and selection modulation mechanisms in context-dependent computation.

Spiking neural networks (SNNs), which are the next generation of artificial neural networks (ANNs), offer a closer mimicry to natural neural networks and hold promise for significant improvements in ...

Guzman et al. (2017) utilized a dynamic form of a Recurrent Neural Network (RNN) model to predict groundwater levels in the Mississippi River Valley Alluvial aquifer, United States. Eight years of ...

This article extends deep learning frameworks for trajectory prediction tasks by exploring how recurrent encoder–decoder neural networks can be tasked not only to predict but also to yield a ...