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Found 6 papers, 3 papers with code
The Duck's Brain: Training and Inference of Neural Networks in Modern Database Engines
Although database systems perform well in data access and manipulation, their relational model hinders data scientists from formulating machine learning algorithms in SQL.
The Case for Learned Spatial Indexes
This exponential growth in spatial data has led the research community to focus on building systems and applications that can process spatial data efficiently.
RadixSpline: A Single-Pass Learned Index
Recent research has shown that learned models can outperform state-of-the-art index structures in size and lookup performance.
SOSD: A Benchmark for Learned Indexes
A groundswell of recent work has focused on improving data management systems with learned components.
Estimating Cardinalities with Deep Sketches
We introduce Deep Sketches, which are compact models of databases that allow us to estimate the result sizes of SQL queries.
Databases
Learned Cardinalities: Estimating Correlated Joins with Deep Learning
We describe a new deep learning approach to cardinality estimation.
Databases
