interestingly, the variables λ_X and λ_Y can be interpreted as "encoder-decoder" pairs giving the conditional distributions of Y|X and X|Y.
we ran some experiments to illustrate this, e.g., here we use SOMCOT to discover the latent structure of a block Markov chain without any prior knowledge
9/n

new work on computing distances between stochastic processes ***based on sample paths only***! we can now:
- learn distances between Markov chains
- extract "encoder-decoder" pairs for representation learning
- with sample- and computational-complexity guarantees
read on for some quick details..
1/n

posting something nice soon