148 citations · 1.1k across the 40 of their papers we have counts for
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cs.LG2026★ 13 cited
On two ways to use determinantal point processes for Monte Carlo integration
Guillaume Gautier, Rémi Bardenet, Michal Valko
The standard Monte Carlo estimator of relies on independent samples from and has variance of order . Replacing the samples with a…
cs.LG2021
Nonparametric estimation of continuous DPPs with kernel methods
Michaël Fanuel, Rémi Bardenet
Determinantal Point Process (DPPs) are statistical models for repulsive point patterns. Both sampling and inference are tractable for DPPs, a rare feature among models with negativ…
cs.LG2018★ 1 cited
DPPy: Sampling DPPs with Python
Guillaume Gautier, Guillermo Polito, Rémi Bardenet +1
Determinantal point processes (DPPs) are specific probability distributions over clouds of points that are used as models and computational tools across physics, probability, stati…