Can a neural network be constructed entirely from DNA and yet learn in the same way as its silicon-based brethren? Recent ...

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

Self-supervised learning allows a neural network to figure out for itself what matters. The process might be what makes our own brains so successful.

Neural networks are now applied across the spectrum of AI applications while deep learning is reserved for more specialized or advanced AI use cases.

To help them explain the shocking success of deep neural networks, researchers are turning to older but better-understood models of machine learning.

Seeking to explore the capabilities of neural networks for recognizing and predicting motion, a group of researchers led by Hehe Fan developed and tested a deep learning approach based on relative ...

The researchers strengthened their findings with some theoretical results showing that, on some level, such subliminal ...

Deep neural networks will move past their shortcomings without help from symbolic artificial intelligence, three pioneers of deep learning argue in a paper published in the July issue of the ...

Artificial neural networks learn better when they spend time not learning at all Periods off-line during training mitigated 'catastrophic forgetting' in computing systems Date: November 18, 2022 ...