This week, researchers published LIGO findings that hint at the existence of second-generation black holes. Astronomers ...

Abstract: The data-driven sliding mode control (SMC) method proves to be highly effective in addressing uncertainties and enhancing system performance. In our previous work, we implemented a co-design ...

At MIT’s Lincoln Laboratory, a new supercomputer has arrived. TX-GAIN, capable of two AI-exaflops, fuses more than six ...

Artivion (NYSE:AORT) drives innovation in Healthcare Stocks, enhancing its role and impact on the nyse composite index today.

Visual content depicting climate activists emphasizes emotion and disruption, contrasting with the rational, data-driven ...

UC Santa Barbara computer scientist Daniel Lokshtanov is advancing fundamental understanding of computational efficiency through groundbreaking research on quasi-polynomial time algorithms, supported ...

Daniel Lokshtanov’s work explores the limits of what computers can solve, paving the way for advances in artificial intelligence and computational efficiency.

Graph Neural Networks (GNNs) and GraphRAG don’t “reason”—they navigate complex, open-world financial graphs with traceable, multi-hop evidence. Here’s why BFSI leaders should embrace graph-native AI ...

Abstract: In our prior work, we have introduced local graph Fourier frames (LGFFs) as a flexible and powerful modeling and analysis tool for graph signals. The most important practical advantage of ...

The original version of this story appeared in Quanta Magazine. They say a bird in the hand is worth two in the bush, but for computer scientists, two birds in a hole are better still. That’s because ...