A key objective of several neuroscience studies is to understand and model how the dynamics of distinct populations of neurons give rise to specific human and animal behaviors. Many existing methods ...

A new study uses deep linear networks to prove that language undergoes iterated learning to become structured and learnable.

Methods for solving partial differential equations have progressed from analytical solutions to numerical simulations and, ...

In our view, higher-category theory, which possesses the highest degree of abstraction, is a second-level language relative ...

Artificial intelligence might now be solving advanced math, performing complex reasoning, and even using personal computers, but today’s algorithms could still learn a thing or two from microscopic ...

But despite their potential, these systems have struggled to match the accuracy of digital neural networks. A key reason: most photonic systems still mimic the structure and training methods of ...

Discover how predictive analytics uses data-driven models like decision trees and neural networks to forecast outcomes and ...

A hunk of material bustles with electrons, one tickling another as they bop around. Quantifying how one particle jostles others in that scrum is so complicated that, beginning in the 1990s, physicists ...