A neural network, which has multiple hidden layers, can also be termed a deep learning algorithm. Deep learning leverages neural networks with several hidden layers, which are useful in handling ...

This collection welcomes submissions on explainability techniques for deep learning neural networks, encompassing diverse neural architectures and ensuring broad applicability to different domains.

Deep learning systems—a type of unsupervised machine learning—are increasingly used with neural networks. They’re called “deep learning” because they contain large numbers of neural layers.

Deep neural networks (DNNs), the machine learning algorithms underpinning the functioning of large language models (LLMs) and other artificial intelligence (AI) models, learn to make accurate ...

The neural net “employs a feedforward neural network with a precisely calibrated 4-60-12 architecture and sigmoid activation functions.” This leads to an approximate 85% accuracy being able to ...

In a market where billions are traded every day, predictive accuracy is paramount. By combining adaptive decomposition, deep ...

On the 10th anniversary of key research that led to deep learning breakthroughs, AI luminaries say the 'revolution' will continue.

This study presents a valuable application of a video-text alignment deep neural network model to improve neural encoding of naturalistic stimuli in fMRI. The authors found that models based on ...