An AI-driven digital-predistortion (DPD) framework can help overcome the challenges of signal distortion and energy ...

The challenge posed by the many-body problem in quantum physics originates from the difficulty of describing the nontrivial correlations encoded in the exponential complexity of the many-body wave ...

Article reviewed by Grace Lindsay, PhD from New York University. Scientists design ANNs to function like neurons. 6 They write lines of code in an algorithm such that there are nodes that each contain ...

Artificial intelligence is now part of our daily lives, with the subsequent pressing need for larger, more complex models.

The learning algorithm that enables the runaway success of deep neural networks doesn’t work in biological brains, but researchers are finding alternatives that could. In 2007, some of the leading ...

A team has developed a novel approach for comparing neural networks that looks within the 'black box' of artificial intelligence to help researchers understand neural network behavior. Neural networks ...

Artificial intelligence is now part of our daily lives, with the subsequent pressing need for larger, more complex models.

Neural networks are computing systems designed to mimic both the structure and function of the human brain. Caltech ...

Researchers discuss how mimicking sleep patterns of the human brain in artificial neural networks may help mitigate the threat of catastrophic forgetting in the latter, boosting their utility across a ...

A mechanical neural network composed of beams, motors and sensors can learn to carry out several different tasks, just like its software equivalent, and could lead to aircraft wings that morph during ...