PanMAN data structures compress pangenomes massively, encode evolutionary histories, and enable scalable analysis of millions of genomes.

Engineers at the University of California have developed a new data structure and compression technique that enables the ...

Discover what context graphs are, why they're revolutionizing AI systems, and who's building this trillion-dollar technology ...

Quantum walks sound abstract, but they sit at the center of a very concrete race: who will harness quantum mechanics to solve ...

Abstract: Graph neural networks (GNNs), as a cutting-edge technology in deep learning, perform particularly well in various tasks that process graph structure data. However, their foundation on ...

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 ...

Abstract: This paper focuses on representation learning for dynamic graphs with temporal interactions. A fundamental issue is that both the graph structure and the nodes own their own dynamics, and ...

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 ...

I co-created Graph Neural Networks while at Stanford. I recognized early on that this technology was incredibly powerful. Every data point, every observation, every piece of knowledge doesn’t exist in ...

What if your AI could not only retrieve information but also uncover the hidden relationships that make your data truly meaningful? Traditional vector-based retrieval methods, while effective for ...