Just as GPUs once eclipsed CPUs for AI workloads, Neural Processing Units (NPUs) are set to challenge GPUs by delivering even ...

Deep neural networks will allow signal transfer of nerve cells to be analyzed in real time in the future. That is the result ...

Following the initial success of deep learning models in energy price prediction, we attempt to establish a better architecture of neural networks to improve the prediction accuracy. We propose a ...

Neural networks are potentially massively parallel distributed structures and have the ability to learn and generalize. The neuron is the information processing unit of a neural network and the basis ...

It makes efficient use of deep neural networks in an ensmble setting. It consists of a number of parallel deep neural networks that are made parallel together. Each parallel sub-layer is followed by ...

However, AI models are often used to find intricate patterns in data where the output is not always proportional to the input ...

Some other problems of parallel distributed information processing are also considered, such as a recall process from network memory for large-scale recurrent associative memory neural networks, ...

[Ramin Hasani] and colleague [Mathias Lechner] have been working with a new type of Artificial Neural Network called Liquid Neural Networks, and presented some of the exciting results at a recent ...

"IEEE.tv is an excellent step by IEEE. This will pave a new way in knowledge-sharing and spreading ideas across the globe." ...

Neural network models are pivotal in neuroscience ... Additionally, the algorithm managed the superposition of arc labels—both parallel and antiparallel—to maintain consistent transitions.