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Found 4 papers, 1 papers with code
TransductGAN: a Transductive Adversarial Model for Novelty Detection
Transductive novelty detection on the other hand has only witnessed a recent surge in interest, it not only makes use of the negative class during training but also incorporates the (unlabeled) test set to detect novel examples.
A hierarchical Bayesian model to find brain-behaviour associations in incomplete data sets
In synthetic data, GFA uncovered the underlying shared and specific factors and predicted correctly the non-observed data modalities in complete and incomplete data sets.
Finding the needle in high-dimensional haystack: A tutorial on canonical correlation analysis
Since the beginning of the 21st century, the size, breadth, and granularity of data in biology and medicine has grown rapidly.
Interpreting weight maps in terms of cognitive or clinical neuroscience: nonsense?
Since machine learning models have been applied to neuroimaging data, researchers have drawn conclusions from the derived weight maps.
