Phys.org

Using geometry and physics to explain feature learning in deep neural networks

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 ...
Nature

Architectural optimisation in deep neural networks. Tests of a theoretically inspired method

Deep neural networks (DNNs) are at the forefront of the technological revolution that artificial intelligence is coming with 1. These networks possess the ability to learn complex patterns and ...
Nature

Fast and robust analog in-memory deep neural network training

Analog in-memory computing is a promising future technology for efficiently accelerating deep learning networks. While using in-memory computing to accelerate the inference phase has been studied ...