Artificial intelligence (AI) is increasingly used to analyze medical images, materials data and scientific measurements, but ...

Training artificial intelligence models is costly. Researchers estimate that training costs for the largest frontier models ...

The world’s most powerful supercomputers can now run simulations of billions of neurons, and researchers hope such models ...

This video demonstrates how to model rigid objects using springs in a Python physics simulation. We explore how spring forces approximate rigidity, analyze motion and stability, and visualize the ...

This important study introduces a new biology-informed strategy for deep learning models aiming to predict mutational effects in antibody sequences. It provides solid evidence that separating ...

Abstract: The creation of data-driven models for classification problems requires increasing transparency and inferential explainability, especially in high-stakes domains such as health-care, finance ...

Ashutosh Agarwal is a specialist who connects analytics with practical strategy, who stands out in the era of digital ...

Abstract: Electromagnetic computational imaging (ECI) offers a promising solution to electromagnetic inverse scattering problems (ISPs). Whereas it is challenged by its ill-posed nature and ...

In this work we present two main contributions: the first one is a Python implementation of the discrete approximation of the Laplace-Beltrami operator (LBO) (Belkin et al., 2008) allowing us to solve ...