Discover Denario, the new open-source AI that automates the entire scientific process, from generating hypotheses to ...

Abstract: This paper shows that physics-aware machine learning can construct accurate surrogate models for optimal design, uncertainty quantification, and data assimilation, even when limited training ...

(The Conversation is an independent and nonprofit source of news, analysis and commentary from academic experts.) Since the prize announcement, cheers and excitement have surrounded the home ...

For decades, scientists have relied on structure to understand protein function. Tools like AlphaFold have revolutionized how researchers predict and design folded proteins, allowing for new ...

The Standard Model, depicting the fundamental building blocks of the universe, including top quarks. Courtesy of Cush via Wikimedia Commons Sitong An, a physicist at Carnegie Mellon University, has ...

Visual reasoning tasks challenge artificial intelligence models to interpret and process visual information using both perception and logical reasoning. These tasks span a wide range of applications, ...

Physics and Python stuff. Most of the videos here are either adapted from class lectures or solving physics problems. I really like to use numerical calculations without all the fancy programming ...

Recent developments in machine learning techniques have been supported by the continuous increase in availability of high-performance computational resources and data. While large volumes of data are ...

Artificial intelligence and machine learning projects require a lot of complex data, which presents a unique cybersecurity risk. Security experts are not always included in the algorithm development ...

Main codes for half-cell model, PINN and co-kriging implemented for physics-informed degradation diagnostics project: https://doi.org/10.1016/j.ensm.2024.103343 ...