Wasserstein Learning of Determinantal Point Processes

no code implementations • NeurIPS Workshop LMCA 2020 • Lucas Anquetil, Mike Gartrell, Alain Rakotomamonjy, Ugo Tanielian, Clément Calauzènes

Through an evaluation on a real-world dataset, we show that our Wasserstein learning approach provides significantly improved predictive performance on a generative task compared to DPPs trained using MLE.

Point Processes