Author

H. Lopes

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#machine learning Preprint Oct 2026

Time-partitioning Gaussian Process Mixture Model

The Time-partitioning Gaussian Process Mixture Model (TPGPMM), a Bayesian nonparametric framework for regime identification and nonstationary prediction that infers such regimes and their within-regime dependence from data, without Markovian assumptions is proposed.

Guilherme Piantino, H. Lopes · 0 citations

Volume-driven time-of-day effects in intraday volatility models

I. Ferreira, Batista Martins, Audronė Virbickaitė et al. · 1 citation