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

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 ...

Neural networks hold this promise, but scientists must use them with caution – or risk discovering that they have solved the wrong problem entirely, writes Janelle Shane Generation game: Images of ...

Scientists at UCL, Google DeepMind and Intrinsic have developed a powerful new AI algorithm that enables large sets of robotic arms to work together faster and smarter in busy industrial settings, ...

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

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 ...

By using a neural network-based decoupling algorithm, the team was able to resolve spectral interference within the existing system, reducing both the complexity and cost of the design.

Deep neural networks can solve the most challenging problems, but require abundant computing power and massive amounts of data.