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Found 3 papers, 3 papers with code
Connecting the Dots: What Graph-Based Text Representations Work Best for Text Classification Using Graph Neural Networks?
Given the success of Graph Neural Networks (GNNs) for structure-aware machine learning, many studies have explored their use for text classification, but mostly in specific domains with limited data characteristics.
On the Quality of Deep Representations for Kepler Light Curves Using Variational Auto-Encoders
In addition, the S-VRAE𝑡 embeds the re-scaling preprocessing of the time series into the model in order to use the Flux standard deviation in the learning of the light curves structure.
Classical Machine Learning Techniques in the Search of Extrasolar Planets
The field of astronomical data analysis has experienced an important paradigm shift in the recent years.
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