Deep Neural Networks are the more computationally powerful cousins to regular neural networks. Learn exactly what DNNs are and why they are the hottest topic in machine learning research. The term ...

Training a neural network is the process of finding a set of weight and bias values so that for a given set of inputs, the outputs produced by the neural network are very close to some target values.

The simplified approach makes it easier to see how neural networks produce the outputs they do. A tweak to the way artificial neurons work in neural networks could make AIs easier to decipher.

When we design a skyscraper we expect it will perform to specification: that the tower will support so much weight and be able to withstand an earthquake of a certain strength. But with one of the ...

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 ...

Security researchers have devised a technique to alter deep neural network outputs at the inference stage by changing model weights via row hammering in an attack dubbed ‘OneFlip.’ A team of ...

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 ...