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Found 4 papers, 1 papers with code
Learning to Simulate: Generative Metamodeling via Quantile Regression
In this paper, we propose a new metamodeling concept, called generative metamodeling, which aims to construct a "fast simulator of the simulator".
Clustering by the Probability Distributions from Extreme Value Theory
In contrast, the GPD fits the distribution of distance to the centroid exceeding a sufficiently large threshold, leading to a more stable performance of GPD k-means.
Incrementally Zero-Shot Detection by an Extreme Value Analyzer
However, zero-shot learning models assume that all seen classes should be known beforehand, while incremental learning models cannot recognize unseen classes.
Extreme Value k-means Clustering
We thus propose a novel algorithm called Extreme Value k-means (EV k-means), including GEV k-means and GPD k-means.
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