Integrating Transformer and Autoencoder Techniques with Spectral Graph Algorithms for the Prediction of Scarcely Labeled Molecular Data
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DOI: 10.48550/arxiv.2211.06759
Abstract: In molecular and biological sciences, experiments are expensive, time-consuming, and often subject to ethical constraints. Consequently, one often faces the challenging task of predicting desirable properties from small data sets or scarcely-labeled data sets. Although… read more here.
Keywords: scarcely labeled; transformer autoencoder; labeled data; integrating transformer ... See more keywords