Researchers have developed a new tool, bimodularity, that adds directionality to community detection in networks.

Scientists at UCL, Google DeepMind and Intrinsic have developed a powerful new AI algorithm that enables large sets of ...

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 ...

Google LLC today detailed RigL, an algorithm developed by its researchers that makes artificial intelligence models more hardware-efficient by shrinking them. Neural networks are made up of so ...

A new technical paper titled “Exploring Neuromorphic Computing Based on Spiking Neural Networks: Algorithms to Hardware” was published by researchers at Purdue University, Pennsylvania State ...

The algorithm uses supervised learning with known histopathology diagnoses (malignant and nonmalignant) as the labels for algorithm training. MIA3G is a classification deep feedforward neural network ...

Recently, Anhui Zhongji Star Electronic Technology Co., Ltd. submitted a patent application titled "Dynamic Control Method ...

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.

Artificial neural networks process data in a manner similar to the human brain. Written by eWEEK content and product recommendations are editorially independent. We may make money when you click ...

On a more basic level, [Gigante] did just that, teaching a neural network to play a basic driving game with a genetic algorithm. The game consists of a basic top-down 2D driving game.