Neural networks have emerged as a powerful framework for addressing complex problems across numerous scientific domains. In particular, the interplay between neural network models and constraint ...

Recent advances at the intersection of neural networks and inverse scattering problems have transformed traditional approaches to imaging and material characterisation. Inverse scattering involves ...

Neural networks are computing systems designed to mimic both the structure and function of the human brain. Caltech researchers have been developing a neural network made out of strands of DNA instead ...

Deep neural networks have gained fame for their capability to process visual information. And in the past few years, they have become a key component of many computer vision applications. Among the ...

Deep neural networks have a huge advantage: They replace “feature engineering”—a difficult and arduous part of the classic machine learning cycle—with an end-to-end process that automatically learns ...

Differential equations are fundamental tools in physics: they are used to describe phenomena ranging from fluid dynamics to general relativity. But when these equations become stiff (i.e. they involve ...

Generative artificial intelligence (AI) — such as ChatGPT and Dalle-2 — is undoubtedly one of the most groundbreaking and discussed technologies in recent history. Its applications and related issues ...

Deep neural networks have gained fame for their capability to process visual information. And in the past few years, they have become a key component of many computer vision applications. Among the ...

Researchers from the Institute of Cosmos Sciences of the University of Barcelona (ICCUB) have developed a new framework based ...

As the name suggests, neural networks are inspired by the brain. A neural network is designed to mimic how our brains work to ...