A new framework that causes artificial neural networks to mimic how real neural networks operate in the brain has been ...

Deep learning uses multi-layered neural networks that learn from data through predictions, error correction and parameter ...

Can a machine truly outthink the volatile winds emitted by the Sun? NYU Abu Dhabi researchers have shown it can by achieving a 45% improvement in predictive accuracy over existing operational models ...

The human brain isn’t a blank slate waiting to be written by experience, according to research that challenges the century-old Tabula Rasa theory. The study shows that neurons grown in laboratory ...

The true environment in which the agent will ultimately operate is “hidden” in this set. This means the agent must learn a controller that performs well across all possible environments. The challenge ...

Modern neural networks, with billions of parameters, are so overparameterized that they can "overfit" even random, ...

We have explained the difference between Deep Learning and Machine Learning in simple language with practical use cases.

This correspondence between brain state and brain responsiveness (statedependent responses) is outlined at different scales from the cellular and circuit level, to the mesoscale and macroscale level.

Nexus proposes higher-order attention, refining queries and keys through nested loops to capture complex relationships.

Pricing continues to be one of the most crucial decisions retailers face. Set prices too high, and customers drift away; too ...

Humans and most other animals are known to be strongly driven by expected rewards or adverse consequences. The process of ...