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.
Furthermore, EHRs serve as the primary interface for clinicians and laboratories to order tests and receive results, but molecular profiling results and their interpretation often exist outside of the ...
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