From greedy shortcuts to dynamic programming guarantees, algorithm design techniques are the backbone of efficient problem-solving in computer science. Understanding when and how to apply each ...

Graph theory and computational modeling reveal that neural network architecture biases the male Caenorhabditis elegans brain toward prioritized sexual behaviors.

Faculty and students from the Department of Mathematical Sciences recently represented the U of A at two regional conferences focused on mathematics and mathematics education, highlighting innovative ...

Systematic reviews with network meta-analysis (NMA) have potential biases in their conduct, analysis, and interpretation. If the results or conclusions of an NMA are integrated into policy or practice ...

The Heisenberg uncertainty principle puts a limit on how precisely we can measure certain properties of quantum objects. But researchers may have found a way to bypass this limitation using a quantum ...

The recent past has seen an increasing interest in Heterogeneous Graph Neural Networks (HGNNs), since many real-world graphs are heterogeneous in nature, from citation graphs to email graphs. However, ...

ABSTRACT: Machine learning (ML) has become an increasingly central component of high-energy physics (HEP), providing computational frameworks to address the growing complexity of theoretical ...

The prediction of the properties of crystal materials has always been a core issue in materials science and solid-state physics. With the rapid development of computer simulation techniques and ...

Abstract: In this letter, we propose a meta-learning-based fast adversarial training method to address the vulnerability of graph neural network (GNN) based resource allocation method to adversarial ...

Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. The interaction between circular RNAs (circRNAs) and RNA-binding proteins (RBPs) plays ...