Counting and uniform sampling of directed acyclic graphs (DAGs) from a Markov equivalence class are fundamental tasks in graphical causal analysis. In this paper, we show that these can be performed polynomial time, solving long-standing open problem area. Our algorithms effective easily implementable. Experimental results the significantly outperform state-of-the-art methods.

An alternative to conventional uniform sampling is that of time encoding, which converts continuous-time signals into streams trigger times. This gives rise Event-Driven Sampling (EDS) models. The data-driven nature EDS acquisition advantageous in terms power consumption and resolution inspired by the information representation biological nervous systems. If an analog signal outside a predefine...