The design of methods for inference from time sequences has traditionally relied on statistical models that describe the relation between a latent desired sequence and observed one. A broad family model-based algorithms have been derived to carry out at controllable complexity using recursive computations over factor graph representing underlying distribution. An alternative model-agnostic appr...