Hi Jouni! You may find interesting these other papers of ours: - The ALENEX21 paper "A 'learned' approach to quicken and compress rank/select dictionaries" (h

Hi Jouni! You may find interesting these other papers of ours: - The ALENEX21 paper "A 'learned' approach to quicken and compress rank/select dictionaries" (http://pages.di.unipi.it/vinciguerra/publication/learned-rank-select/ http://pages.di.unipi.it/vinciguerra/publication/learned-ran..., https://github.com/gvinciguerra/la_vector https://github.com/gvinciguerra/la_vector), where we introduce a compressed bitvector supporting efficient rank and select queries, which is competitive with several well-established implementations of succinct data structures. - The ICML20 paper "Why are learned indexes so effective?" (http://pages.di.unipi.it/vinciguerra/publication/learned-indexes-effectiveness/ http://pages.di.unipi.it/vinciguerra/publication/learned-ind...) where we prove that, under some general assumptions on the input data, the space of the PGM-index is actually O(n/B^2) whp (versus Θ(n/B) of classic B-trees).