Graph neural networks (GNN) have shown outstanding applications in fields where data is essentially represented as graphs (e.g., chemistry, biology, and recommendation systems). In this vein, ...

Context engineering—the art of shaping the data, metadata, and relationships that feed AI—may become the most critical ...

This important study presents a new method for longitudinally tracking cells in two-photon imaging data that addresses the specific challenges of imaging neurons in the developing cortex. It provides ...

Start with the basics: get a handle on what AI is, why it matters, and how it’s used in the real world. Make a plan: figure ...

By learning the relevant features of clinical images along with the relationships between them, the neural network can outperform more traditional methods.

Rats exhibit significant recovery of locomotor function following incomplete spinal cord injuries, albeit with altered gait expression and reduced speed and stepping frequency. These changes likely ...

Free platforms like Coursera and Google AI offer beginner courses in artificial intelligence.• Python is the most used ...

However, as dynamic network literature stems from diverse fields and makes use of inconsistent terminology, it is challenging to navigate. Meanwhile, graph neural networks (GNNs) have gained a lot of ...

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Explore the fascinating world of convolutional neural networks (CNNs) and uncover how they’ve revolutionized the field of computer vision and deep learning. Understand the building blocks of CNNs and ...