Deep neural networks are at the heart of artificial intelligence, ranging from pattern recognition to large language and ...

Researchers have uncovered how primate brains transform flat, 2D visual inputs into rich, 3D mental representations of ...

By learning the relevant features of clinical images along with the relationships between them, the neural network can outperform more traditional methods.

Caltech scientists have found a fast and efficient way to add up large numbers of Feynman diagrams, the simple drawings ...

Rats exhibit significant recovery of locomotor function following incomplete spinal cord injuries, albeit with altered gait expression and reduced speed and stepping frequency. These changes likely ...

Neuroscientists want to understand how individual neurons encode information that allows us to distinguish objects, like telling a leaf apart from a rock. But they have struggled to build ...

The Large Hadron Collider is one of the biggest experiments in history, but it’s also one of the hardest to interpret. Unlike ...

Researchers from Skoltech and AIRI Institute have shown how machine learning can speed up the development of new materials for solid-state lithium-ion batteries. These are an emerging energy storage ...

Brain-inspired spiking neural networks bring real-time AI to edge devices, boosting performance, reducing power use, and enhancing data privacy.

Neural processing unts (NPUs) are the latest chips you might find in smartphones and laptops — but what are they ard why are they so important?

Despite the widespread success of neural networks, their susceptibility to adversarial examples remains a significant challenge. Adversarial training (AT) has emerged as an effective approach to ...