PilotScope is a middleware to bridge the gaps of deploying AI4DB (Artificial Intelligence for Databases) algorithms into actual database systems.

Neural Relation Understanding: neural cardinality estimators for tabular data

Fast HyperLogLog for Python.

Implementation of DeepDB: Learn from Data, not from Queries!

Dynatrace hash library for Java

Estimating k-mer coverage histogram of genomics data

State-of-the-art neural cardinality estimators for join queries

Paper about the estimation of cardinalities from HyperLogLog sketches

Union, intersection, and set cardinality in loglog space

SetSketch: Filling the Gap between MinHash and HyperLogLog

Paper related to AI4DB techniques

A Unified Deep Model of Learning from both Data and Queries for Cardinality Estimation

A pytorch implementation for FACE: A Normalizing Flow based Cardinality Estimator

A Python library for efficient feature ranking and selection on sparse data sets.

Fast Cardinality Estimation of Multi-Join Queries Using Sketches

A crate for estimating the cardinality of distinct elements in a stream or dataset.

Code for Local Deep Learning Models for Cardinality Estimation

An implementation of the algorithms presented in the paper "Cardinality Estimation Done Right: Index-Based Join Sampling"

[VLDB'22] Cardinality Estimation of Approximate Substring Queries using Deep Learning.