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Found 5 papers, 2 papers with code
Interpretable and intervenable ultrasonography-based machine learning models for pediatric appendicitis
Appendicitis is among the most frequent reasons for pediatric abdominal surgeries.
On the Limitations of Multimodal VAEs
Multimodal variational autoencoders (VAEs) have shown promise as efficient generative models for weakly-supervised data.
Deep Conditional Gaussian Mixture Model for Constrained Clustering
Constrained clustering has gained significant attention in the field of machine learning as it can leverage prior information on a growing amount of only partially labeled data.
A Probabilistic Approach to Constrained Deep Clustering
Clustering with constraints has gained significant attention in the field of semi-supervised machine learning as it can leverage partial prior information on a growing amount of unlabelled data.
Generation of Differentially Private Heterogeneous Electronic Health Records
In this work, we explore using Generative Adversarial Networks to generate synthetic, heterogeneous EHRs with the goal of using these synthetic records in place of existing data sets for downstream classification tasks.
