Binary digits and circuit patterns forming a silhouette of a head. Neural networks and deep learning are closely related artificial intelligence technologies. While they are often used in tandem, ...

Overview A mix of beginner and advanced-level books to suit various learning needs.Each book blends theory with practical ...

In oncology and cardiology, AI’s strength lies in deep learning techniques applied to imaging and genomic data. Convolutional ...

At a time when conflict and division dominate the headlines, a new study from UCLA finds remarkable similarities in how mice ...

Deep learning approaches, particularly convolutional neural networks (CNNs) and other architectures, were used in 49 papers. These models excel at image-based tasks such as land cover classification, ...

The 5-day International Workshop on Deep Learning and Artificial Intelligence (DLAI9), held in collaboration with the Asia-Pacific Neural Networks Society (APNNS) and IEEE Geoscience and Remote ...

Recently, researchers introduced a new representation learning framework that integrates causal inference with graph neural networks—CauSkelNet, which can be used to model the causal relationships and ...

A landmark has been reached in the field of physics and artificial intelligence with the successful resolution of a 50-year-old science problem. The neural network, developed by Alphabet subsidiary, ...