Extended Data Fig. 3: Generative modeling of ‘synthetic’ trajectories.
From: Learning biophysical determinants of cell fate with deep neural networks
For each synthetic trajectory we start by encoding a real image as a starting point. Next, we take a random walk in the latent space. These trajectories in latent space are used as inputs to the TCN. Here, we also use the decoder to generate image sequences that represent the random walks in latent space.
