Work

Entropy Coding of Unordered Data Structures

Year: 2024

Type: preprint

Abstract: We present shuffle coding, a general method for optimal compression of sequences of unordered objects using bits-back coding. Data structures that can be compressed using shuffle coding include multisets, graphs, hypergraphs, and others. We release an implementation that can easily be adapted to different data types and statistical models, and demonstrate that our implementation achieves state-of-the-art compression rates on a range of graph datasets including molecular data.

Source: arXiv (Cornell University)

DOI: 10.48550/arxiv.2408.08837

Authors: Kunze, Julius, Severo, Daniel, Zani, Giulio, van de Meent, Jan-Willem, Townsend, James

Institutions: University College London, University of Toronto, Vector Institute, University of Amsterdam

Language: English

Topic: Algorithms and Data Compression

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: green

Funder: Nederlandse Organisatie voor Wetenschappelijk Onderzoek

Award: Neural networks for efficient storage and communication of information

OpenAlex ID: W4402501202

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