A secondary purpose of this repository is to provide a generalized graph API that enables implementation of a very wide range of in-memory graph algorithms including basic methods for reading, writing ...

Researchers have developed an AI-driven framework that improves genomic surveillance by identifying emerging virus variants ...

Combinatorial optimization problems are often encountered in real-world applications, including logistics, scheduling and ...

Single-cell RNA-seq AI analysis has become the default way to make sense of the millions of expression measurements a single experiment can now generate. Turning raw sequencing counts into ...

New Iterative Block Particle Filter algorithm makes genomic surveillance faster, cheaper and more scalable, improving early ...

Context graphs, graph memory, and ontologies for AI are converging. What does this mean for enterprise AI in 2026?

But by this spring, Khan had admitted that the release of Khanmigo was “a non-event” for many kids. Although access exploded, ...

Abstract: We propose a convex-concave programming approach for the labeled weighted graph matching problem. The convex-concave programming formulation is obtained by rewriting the weighted graph ...

Jeremiah Blocki, jblocki+451@cs.cmu.edu: Monday @ 3:30 PM. GHC 7th floor lounge. Students can email me if they want to meet at a different time. Anvesh Komuravelli, anvesh+451@cs.cmu.edu: Friday @ 4 ...

Building a utility-scale quantum computer that can crack one of the most vital cryptosystems—elliptic curves—doesn’t require nearly the resources anticipated just a year or two ago, two independently ...