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 ...
Researchers demonstrate a novel method for transforming continuous time crystals into discrete ones using subharmonic injection locking, offering new insights into symmetry breaking and control in ...
There is a long tradition in using genetically based color polymorphisms in natural populations to study evolutionary processes. Despite growing evidence for continuous phenotypic variation within ...
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