Princeton researchers have developed a new tool to speed the discovery of advanced materials known as metal organic ...

A team led by Egbert Zojer from the Institute of Solid State Physics at Graz University of Technology (TU Graz) has now significantly improved these simulations using machine learning, which greatly ...

The simulation of the heat conduction properties of MOFs is carried out with very high accuracy using the new method. Credit: IF - TU Graz The simulation of the heat conduction properties of MOFs is ...

Since 2021, Korean researchers have been providing a simple software development framework to users with relatively limited ...

The presentation below, “Survey of Available Machine Learning Frameworks,” is provided by Brendan Herger of CapitalOne as part of the H2O World 2015 conference. Learning a new modeling framework is ...

For his research in machine learning-based electron density prediction, Michigan Tech researcher Susanta Ghosh has been recognized with one of the National Science Foundation's highest honors. The NSF ...

An interdisciplinary team of researchers has developed a machine learning framework that uses limited water quality samples to predict which inorganic pollutants are likely to be present in a ...

TrialTranslator uncovers the survival gap for high-risk patients and offers a path to better cancer research. Study: Evaluating generalizability of oncology trial results to real-world patients using ...