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The Nystr\"om method for functional quantization with an application to the fractional Brownian motion

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arxiv 1009.1241 v1 pith:VF6HRQR2 submitted 2010-09-07 math.PR

Sylvain Corlay (PMA) This is my paper · ORCID
classification math.PR
keywords brownianfractionalmotionfunctionalmethodnystroptimalquantization
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In this article, the so-called "Nystr\"om method" is tested to compute optimal quantizers of Gaussian processes. In particular, we derive the optimal quantization of the fractional Brownian motion by approximating the first terms of its Karhunen-Lo\`eve decomposition. A numerical test of the "functional stratification" variance reduction algorithm is performed with the fractional Brownian motion.

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  1. Winner-takes-all for Multivariate Probabilistic Time Series Forecasting

    cs.LG 2025-06 conditional novelty 5.0 of 10

    TimeMCL uses Winner-Takes-All training of multiple heads to quantize the conditional distribution of future time series, producing diverse forecasts at low inference cost.

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