Self-Organizing Maps

Also known as SOM, MAP

Overview

Self-Organizing Maps project high-dimensional examples onto a low-dimensional grid, updating each best-matching unit and its neighbors so nearby inputs tend to remain nearby on the map. Variants include growing and hierarchical maps, SOM-based vector quantization, and optimized or GPU- and distributed implementations for large, sparse, and streaming datasets. They are used for exploratory analysis and as components in tasks such as continual learning, local conformal calibration, and representation learning, with performance assessed through measures such as quantization error and neighborhood preservation as well as task-specific benchmarks. A central tension is scaling and adapting maps without losing useful topology; moreover, preserving structure does not guarantee fair representations, since maps can reveal sensitive attributes absent from training labels.

Latest papers

CardsList

15 papers1 paper in the last four weeks, against 2 the four weeks before. 0.0% of all new papers.

  1. Modeling bilingual naming performance through laterally-connected SOMs

    Oct 16, 2026Divya Prabhakaran, Uli Grasemann, Erie Shivers +3Lexical RetrievalComputational Cognitive Modeling

  2. From 80x to 385x: A Best-Matching-Unit Search at the L2 Roof, Measured Against a Symmetrically Tuned Baseline

    Sep 4, 2026Andrew James AmosGPU Kernel OptimizationSelf-Organizing Maps

  3. Unsupervised Continual Learning with Growing Self-Organizing Maps and Synthetic Replay

    Aug 27, 2026Pujan Thapa, Alexander Ororbia, Travis DesellReplay-Based Continual LearningClass-Incremental Learning

  4. TabSOM: A tabular-to-image encoding method based on self-organizing maps

    Aug 13, 2026David Chushig-Muzo, María Ángeles Rodríguez de Cara, Eva Milara +3Tabular MLSelf-Organizing Maps

  5. Queryable Self-Organizing Maps: A Database Abstraction for Topology-Driven Data Exploration

    Jul 24, 2026Denis Mayr Lima Martins, Gottfried VossenSelf-Organizing MapsDatabase Systems

  6. Motion Primitive Discovery in a Humanoid Robot via Self-Organising Maps for Phase Recognition

    Jul 21, 2026Radovan Gregor, Igor FarkašRoboticsSelf-Organizing Maps

  7. Self-Organized Conformal Prediction: Reducing Regional Coverage Gaps with Unsupervised Group Discovery

    Jun 28, 2026Louis Berthier, Ahmed Shokry, Maxime Moreaud +2Group-Conditional Conformal PredictionConformal Prediction

  8. parHSOM: A novel parallel Hierarchical Self-Organizing Map implementation

    May 4, 2026Rebekah Lane, Logan Cummins, Andy Perkins +3Network Intrusion DetectionSelf-Organizing Maps

  9. FloatSOM: GPU-Accelerated, Distributed, Topology-Flexible Self-Organizing Maps

    Apr 29, 2026Tony Xu, Sarah Klamt, Katherine Turner +3GPU AccelerationHigh-Performance Computing

  10. Self-Organizing Maps with Optimized Latent Positions

    Apr 15, 2026Seiki Ubukata, Akira Notsu, Katsuhiro HondaSelf-Organizing MapsTopological Mapping

  11. SOM-VQ: Topology-Aware Tokenization for Interactive Generative Models

    Feb 24, 2026Alessandro Londei, Denise Lanzieri, Matteo BenatiVector-Quantized Variational AutoencoderTopological Representation Learning

  12. SOMtime the World Ain′'t Fair: Violating Fairness Using Self-Organizing Maps

    Feb 20, 2026Joseph Bingham, Netanel Arussy, Dvir AranUnsupervised LearningAlgorithmic Fairness