Empirical evaluation of GMM, GAN, and VAE models for synthesizing diverse task-dependent fMRI images shows they can augment classifiers with performance gains complementary to the choice of predictive model.
Learning a probabilistic latent space of object shapes via 3d generative-adversarial modeling,
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.CV 1years
2019 1verdicts
UNVERDICTED 1representative citing papers
citing papers explorer
-
FMRI data augmentation via synthesis
Empirical evaluation of GMM, GAN, and VAE models for synthesizing diverse task-dependent fMRI images shows they can augment classifiers with performance gains complementary to the choice of predictive model.