It mimics how biological neurons work in a human brain and develops an adaptive system that continuously improves based on ...

How can we characterize the dynamics of neural networks with recurrent ... Hopfield's work inspired a new generation of recurrent network models; one early example was a learning algorithm that ...

The more lottery tickets you buy, the higher your chances of winning, but spending more than you win is obviously not a wise ...

This essay by the team behind a leading logical model shows the machine’s work, and theirs, in a poignant way that invites us ...

The deep neural network models that power today's most demanding machine-learning applications have grown so large and ...

Researchers find evidence of superfluidity in low-density neutron matter by using highly flexible neural-network ...

Research by astronomers and computer scientists at the University of Hawaiʻi Institute for Astronomy (IfA) could ...