Overview: Master deep learning with these 10 essential books blending math, code, and real-world AI applications for lasting expertise.From neural networks to N ...

In recent years, as the field of deep learning has matured, a small but growing group of researchers and technologists has begun to question the prevailing assumptions behind neural networks. Among ...

As an emerging technology in the field of artificial intelligence (AI), graph neural networks (GNNs) are deep learning models designed to process graph-structured data. Currently, GNNs are effective ...

During my first semester as a computer science graduate student at Princeton, I took COS 402: Artificial Intelligence. Toward the end of the semester, there was a lecture about neural networks. This ...

The TLE-PINN method integrates EPINN and deep learning models through a transfer learning framework, combining strong physical constraints and efficient computational capabilities to accurately ...

Deep learning is increasingly used in financial modeling, but its lack of transparency raises risks. Using the well-known ...

Lightweight convolutional neural networks improved lung cancer classification accuracy in histopathological images while ...

Type in a question to ChatGPT and an answer will materialise. Put a prompt into DALL-E 3 and an image will emerge. Click on TikTok’s “for you” page and you will be fed videos to your taste. Ask Siri ...

Previously met with skepticism, AI won scientists a Nobel Prize for Chemistry in 2024 after they used it to solve the protein folding and design problem, and it has now been adopted by biologists ...

Integrating deep learning in optical microscopy enhances image analysis, overcoming traditional limitations and improving classification and segmentation tasks.