Abstract: Graph-based methods have demonstrated strong performance in multi-view clustering (MVC) due to their capability to capture complex data structures. Among these, discrete spectral embedding ...

Combinatorial structures such as set systems, hypergraphs and families of finite objects form a unifying framework for extremal problems that probe how local intersection constraints govern global ...

Abstract: Integrating Large Language Models (LLMs) with Graph Neural Networks (GNNs) has emerged as a dominant paradigm for representation learning on Text-Attributed Graphs (TAGs). Existing ...

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. In addition, Nature has recently ...

When you're setting out to get a new gaming PC or laptop, you've probably noticed there are quite a few models out there without an Nvidia or AMD graphics chip. These devices usually come with an ...

Graphs are everywhere. From technology to finance, they often model valuable information such as people, networks, biological pathways and more. Often, scientists and technologists need to come up ...

Representing the brain as a complex network typically involves approximations of both biological detail and network structure. Here, we discuss the sort of biological detail that may improve network ...

CEO Sam Altman called a strange graph in its GPT-5 presentation a ‘mega chart screwup.’ CEO Sam Altman called a strange graph in its GPT-5 presentation a ‘mega chart screwup.’ is a senior reporter ...