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Found 3 papers, 1 papers with code
Multiple Domain Causal Networks
Finally, we justify our approach by providing theoretical analyses that demonstrate that MDCN improves on the generalization bound of the new, unobserved target center.
AugmentedPCA: A Python Package of Supervised and Adversarial Linear Factor Models
Deep autoencoders are often extended with a supervised or adversarial loss to learn latent representations with desirable properties, such as greater predictivity of labels and outcomes or fairness with respects to a sensitive variable.
Adversarial Factor Models for the Generation of Improved Autism Diagnostic Biomarkers
Second, we show this same model can be used to learn a disentangled representation of multimodal biomarkers that results in an increase in predictive performance.
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