Many models such as Long Short Term Memory (LSTMs), Gated Recurrent Units (GRUs) and transformers have been developed to classify time series data with the assumption that events in a sequence are ordered. On other hand, fewer for set based inputs, where order does not matter. There several use cases is given partially-ordered sequences because of granularity or uncertainty stamps. We introduce...

A permutation $\pi$ contains a pattern $\sigma$ if and only there is subsequence in with its letters the same relative order as those $\sigma$. Partially ordered patterns (POPs) provide convenient way to denote which of some does not matter. This paper elucidates connections between avoidance sets few POPs other combinatorial objects, directly answering five open questions posed by Gao Kitaev 2...