Joint inference of discrete and continuous factors captures variability across and within cell types
We developed mixture model inference with discrete-coupled autoencoders (MMIDAS), an unsupervised variational framework that jointly learns discrete clusters and continuous cluster-specific ...
Understanding the nature and extent of cellular diversity in the brain is key to unraveling the complexity of neural circuits, their connectivity and roles in behavior, in health and disease 1,2,3.
Data analysis is a fundamental process in any project. However, data can be lumped into different types, with categorical and continuous data seeming almost opposed at first glance. That said, ...
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