Researchers have developed an algorithm to train an analog neural network just as accurately as a digital one, enabling the development of more efficient alternatives to power-hungry deep learning ...

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

The Journal of Real Estate Research, Vol. 40, No. 3 (July – September 2018), pp. 375-418 (44 pages) This study extended the use of artificial neural networks (ANNs) training algorithms in mass ...

Neuromorphic computing systems, encompassing both digital and analog neural accelerators, promise to revolutionize AI ...

Researchers are training neural networks to make decisions more like humans would. This science of human decision-making is only just being applied to machine learning, but developing a neural network ...

Researchers have devised a way to make computer vision systems more efficient by building networks out of computer chips’ logic gates. Networks programmed directly into computer chip hardware can ...

Combinatorial generalization—the ability to understand and produce novel combinations of already familiar elements—is considered to be a core capacity of the human mind and a major challenge to neural ...

The initial research papers date back to 2018, but for most, the notion of liquid networks (or liquid neural networks) is a new one. It was “Liquid Time-constant Networks,” published at the tail end ...

Our species owes a lot to opposable thumbs. But if evolution had given us extra thumbs, things probably wouldn’t have improved much. One thumb per hand is enough. Not so for neural networks, the ...