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Found 3 papers, 3 papers with code
Differentiable Random Partition Models
Partitioning a set of elements into an unknown number of mutually exclusive subsets is essential in many machine learning problems.
Anomaly Detection in Echocardiograms with Dynamic Variational Trajectory Models
The introduced method takes advantage of the periodic nature of the heart cycle to learn three variants of a variational latent trajectory model (TVAE).
Learning Group Importance using the Differentiable Hypergeometric Distribution
We introduce reparameterizable gradients to learn the importance between groups and highlight the advantage of explicitly learning the size of subsets in two typical applications: weakly-supervised learning and clustering.
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