Understanding defect dynamics and evolution in high entropy alloys (HEAs) s is complicated due to the wide and intricate configurational space in HEAs. Machine learning techniques have significant ...
This is a preview. Log in through your library . Abstract We outline a new lower bound on graph entropy and discuss some of its applications. In particular, our results allow us to calculate the graph ...
Using a new physics-informed machine learning approach, researchers discovered two new high-entropy alloys with extremely low thermal expansion, a new study reports. The approach could represent a ...
This is a preview. Log in through your library . Abstract Active learning (AL) technique is the classification of remote sensing images, where collecting efficient training data is costly in terms of ...
The unprecedented explosion in the amount of information we are generating and collecting, thanks to the arrival of the internet and the always-online society, powers all the incredible advances we ...
The updated graph database-as-a-service (DBaaS) will come with visual analytics and machine learning tools, made accessible via the TigerGraph Suite. Dubbed TigerGraph Insights, the visual analytics ...
In an article recently published in the open-access journal npj Computational Materials, researchers discussed the intelligent framework based on machine learning (ML) for finding refractory ...
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