Evolution of artificial intelligence for application in contemporary materials science
Contemporary materials science has seen an increasing application of various artificial
intelligence techniques in an attempt to accelerate the materials discovery process using …
intelligence techniques in an attempt to accelerate the materials discovery process using …
Structure-aware graph neural network based deep transfer learning framework for enhanced predictive analytics on diverse materials datasets
Modern data mining methods have demonstrated effectiveness in comprehending and
predicting materials properties. An essential component in the process of materials …
predicting materials properties. An essential component in the process of materials …
JARVIS-Leaderboard: a large scale benchmark of materials design methods
Lack of rigorous reproducibility and validation are significant hurdles for scientific
development across many fields. Materials science, in particular, encompasses a variety of …
development across many fields. Materials science, in particular, encompasses a variety of …
Hybrid-LLM-GNN: integrating large language models and graph neural networks for enhanced materials property prediction
Graph-centric learning has attracted significant interest in materials informatics. Accordingly,
a family of graph-based machine learning models, primarily utilizing Graph Neural Networks …
a family of graph-based machine learning models, primarily utilizing Graph Neural Networks …
Physics-based data-augmented deep learning for enhanced autogenous shrinkage prediction on experimental dataset
Prediction of the autogenous shrinkage referred to as the reduction of apparent volume of
concrete under seal and isothermal conditions is of great significance in the service life …
concrete under seal and isothermal conditions is of great significance in the service life …
Simultaneously improving accuracy and computational cost under parametric constraints in materials property prediction tasks
Modern data mining techniques using machine learning (ML) and deep learning (DL)
algorithms have been shown to excel in the regression-based task of materials property …
algorithms have been shown to excel in the regression-based task of materials property …
Deep Learning Methodologies for Limited Resources Scenarios in Materials Informatics
V Gupta - 2023 - search.proquest.com
Modern deep learning and data mining techniques have demonstrated their effectiveness to
comprehend and help solve real-life problems associated with various research fields …
comprehend and help solve real-life problems associated with various research fields …