Binary digits and circuit patterns forming a silhouette of a head. Neural networks and deep learning are closely related artificial intelligence technologies. While they are often used in tandem, ...

Information Theory Meets Deep Neural Networks: Theory and Applications. The previous volume can be viewed here: Volume I Deep Neural Networks (DNNs) have become one of the most popular research ...

Biological neural networks are immensely complex systems underlying all aspects of cognition and behavior. Despite significant advances in neuroscience, a ...

The use of deep learning has grown rapidly over the past decade, thanks to the adoption of cloud-based technology and use of deep learning systems in big data, according to Emergen Research, which ...

A deep learning framework enhances medical image recognition by optimizing RNN architectures with LSTM, GRU, multimodal fusion, and CNN ...

In the machine learning world, the sizes of artificial neural networks — and their outsize successes — are creating conceptual conundrums. When a network named AlexNet won an annual image recognition ...

The Navier–Stokes partial differential equation was developed in the early 19th century by Claude-Louis Navier and George Stokes. It has proved its worth for modelling incompressible fluids in ...

If you care about the future of AI — whether as a developer, investor, founder, or policy‑maker — it’s time to pay attention.

Four thousand five hundred sixty-nine exoplanets are orbiting distant stars elsewhere in the observable universe, and recently a massive batch of 301 exoplanets has been added to that total. ExoMiner ...