26 citations · 35 across the 4 of their papers we have counts for
5 papers
The Case for Learned Spatial Indexes
Varun Pandey, Alexander van Renen, Andreas Kipf +3
Spatial data is ubiquitous. Massive amounts of data are generated every day from billions of GPS-enabled devices such as cell phones, cars, sensors, and various consumer-based appl…
RadixSpline: A Single-Pass Learned Index
Andreas Kipf, Ryan Marcus, Alexander van Renen +4
Recent research has shown that learned models can outperform state-of-the-art index structures in size and lookup performance. While this is a very promising result, existing learn…
SOSD: A Benchmark for Learned Indexes
Andreas Kipf, Ryan Marcus, Alexander van Renen +4
A groundswell of recent work has focused on improving data management systems with learned components. Specifically, work on learned index structures has proposed replacing traditi…
DeepSPACE: Approximate Geospatial Query Processing with Deep Learning
Dimitri Vorona, Andreas Kipf, Thomas Neumann +1
The amount of the available geospatial data grows at an ever faster pace. This leads to the constantly increasing demand for processing power and storage in order to provide data a…
Estimating Cardinalities with Deep Sketches
Andreas Kipf, Dimitri Vorona, Jonas Müller +6
We introduce Deep Sketches, which are compact models of databases that allow us to estimate the result sizes of SQL queries. Deep Sketches are powered by a new deep learning approa…