Active learning represents a transformative paradigm in machine learning, aimed at reducing the annotation burden by selectively querying the most informative data points. This approach leverages ...

With the rapid advancements in computer technology and bioinformatics, the prediction of protein-ligand binding sites has ...

Researchers from The University of Osaka's Institute of Scientific and Industrial Research (SANKEN) have successfully ...

Machine Learning (ML) algorithms have revolutionized various domains by enabling data-driven decision-making and automation.

Understanding the properties of different materials is an important step in material design. X-ray absorption spectroscopy ...

What is the Advancing Innovative Methods to Promote Learning (AIM4Learning) Program? The Advancing Innovative Methods to Promote Learning (AIM4Learning) Program is a $1.54 billion regional program ...

The field of computational materials science has been profoundly transformed by integrating deep learning and other machine learning methodologies. These sophisticated data-driven approaches have ...

Conventional clustering techniques often focus on basic features like crystal structure and elemental composition, neglecting target properties such as band gaps and dielectric constants. A new study ...

This e-learning course was developed under the scope of the IAEA MEREIA Programme. The course offers practical guidance on approaches and methods for radiological environmental impact assessment.The ...