Deep learning variant calling has transformed genomic accuracy. Discover how DeepVariant works, outperforms classical tools, ...

Biologically plausible learning mechanisms have implications for understanding brain functions and engineering intelligent systems. Inspired by the multi-scale ...

Dendritic computation is key to the brain’s ability to integrate information over long timescales. Inspired by this, this study proposes a spiking neural network model that embeds dendritic mechanisms ...

Traditional interwell connectivity analysis methods for water-flooding reservoirs suffer from two major limitations: insufficient integration of seepage physics, leading to poor interpretability, and ...

What is a neural network? A neural network, also known as an artificial neural network, is a type of machine learning that works similarly to how the human brain processes information. Instead of ...

A large-scale randomized trial of texting therapy concluded that its outcomes were as good as video sessions in treating depression. By Ellen Barry One of the most popular mental health innovations of ...

The findings of this study are valuable, offering insights into the neural representation of reversal probability in decision-making tasks, with potential implications for understanding flexible ...

Abstract: This study provides a comparative evaluation of transformer models and Recurrent Neural Networks (RNNs) for text classification. As the complexity of the text data is growing and more ...