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 ...

Graph out-of-distribution (OOD) generalization remains a major challenge in graph neural networks (GNNs). Invariant learning, aiming to extract invariant features across varied distributions, has ...

The 2024 Nobel Prize in Chemistry was recently granted to David Baker, Demis Hassabis and John M. Jumper, renowned for their pioneering works in protein design.

As an emerging technology in the field of artificial intelligence (AI), graph neural networks (GNNs) are deep learning models ...

The Kennedy College of Science, Richard A. Miner School of Computer & Information Sciences, invites you to attend a doctoral dissertation proposal defense by Nidhi Vakil, titled: "Foundations for ...

Researchers at Shanghai Jiao Tong University have made a groundbreaking discovery in the field of Temporal Knowledge Graphs (TKGs), challenging the ...

Examine the AI and computer science courses offered by Tsinghua University in 2026. Learn why Tsinghua is the top university ...

As AI, enterprise adoption, and compliance converge, the ability to compute on sensitive data without exposing it on public ...

Explore how intelligent document processing transforms dark, unstructured data into actionable intelligence—enabling faster ...

Knowledge representation is a fundamental aspect of AI, which allows machines to understand, think, and even make choices similarly to humans. By organizing inf ...

A new chip aims to dramatically reduce energy consumption while accelerating the processing of large amounts of data.