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 ...
Intra-individual processes are thought to continuously unfold across time. For equally spaced time intervals, the discrete-time lag-1 vector autoregressive (VAR(1)) model and the continuous-time ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results