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 ...

The authors point out that quantum computers are still plagued by high gate error rates, low qubit counts, and extremely slow ...

Artificial intelligence (AI) is increasingly prevalent, integrated into phone apps, search engines and social media platforms ...

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 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 ...

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 ...

Article reviewed by Grace Lindsay, PhD from New York University. Scientists design ANNs to function like neurons. 6 They write lines of code in an algorithm such that there are nodes that each contain ...

A team at Carnegie Mellon University is helping kids understand artificial intelligence with a soft, squishy, LED-lit neural ...

Artificial Intelligence (AI) is one area that keeps transforming the process of learning and problem-solving. The AI Math ...