By applying new methods of machine learning to quantum chemistry research, Heidelberg University scientists have made significant strides in computational chemistry. They have achieved a major ...

Extracting and analyzing relevant medical information from large-scale databases such as biobanks poses considerable challenges. To exploit such "big data," attempts have focused on large sampling ...

Assistant Professor of Applied Mathematics Ashesh Chattopadhyay will build AI models to project extreme Earth-system events.

Haoyu Cheng, Ph.D., assistant professor of biomedical informatics and data science at Yale School of Medicine, has developed a new algorithm capable of building complete human genomes using standard ...

Abstract: Identifying positive influence dominating set (PIDS) with the smallest cardinality can produce positive effect with the minimal cost on a social network. The purpose of this article is to ...

We study the problem of estimating the size of a maximum matching in sublinear time. The problem has been studied extensively in the literature and various algorithms and lower bounds are known for it ...

AlphaEvolve uses large language models to find new algorithms that outperform the best human-made solutions for data center management, chip design, and more. Google DeepMind has once again used large ...

We present a new optimization-based method for aggregating preferences in settings in which each voter expresses preferences over pairs of alternatives. Our approach to identifying a consensus partial ...

Abstract: Finding the shortest vector in a lattice is a NP-hard problem. The best known approximation algorithm for this problem is LLL algorithm with the approximation factor of αn-1\2, α≥4\3, which ...