We introduce a new learned-index bloom filter, which we call DeepBloom, for determining probabilistically whether a given record is an element of a set. This structure is an extension (generalization) of a learned-index bloom filter proposed by Kraska et. al (2017), and is designed for read-heavy workloads. More details on our approach and results can be found in our writeup.

This repository contains implementations, tests, and other utilities for DeepBloom and the original Kraska et. al bloom filter.