Prototype-based models in machine learning.

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This Looks Like That, Because ... Explaining Prototypes for Interpretable Image Recognition (2020, background): “One type of such models is prototypical learning [5], which has a transparent, built-in case-based decision making process.”
Prototype-based Neural Network Layers: Incorporating Vector Quantization (2018, methodology): “Most of the methods use the concept of prototypes and are therefore called PBs [15].”
Distribution Density, Tails, and Outliers in Machine Learning: Metrics and Applications (2019, methodology): “, 2016) or coresets (Biehl et al., 2016) to cope with the high dimensionality of a task.”
Classification-by-Components: Probabilistic Modeling of Reasoning over a Set of Components (2019, background): “Prototype-based classiﬁers like Learning Vector Quantizers [9, 10] are more interpretable and can provide insights into their classiﬁcation processes.”