63 citations · 104 across the 4 of their papers we have counts for
Showing 2021Show all
2 papers · 1 filter
cs.LG2021
Parameter Efficient Deep Probabilistic Forecasting
Olivier Sprangers, Sebastian Schelter, Maarten de Rijke
Probabilistic time series forecasting is crucial in many application domains such as retail, ecommerce, finance, or biology. With the increasing availability of large volumes of da…
cs.LG2021★ 41 cited
Probabilistic Gradient Boosting Machines for Large-Scale Probabilistic Regression
Olivier Sprangers, Sebastian Schelter, Maarten de Rijke
Gradient Boosting Machines (GBM) are hugely popular for solving tabular data problems. However, practitioners are not only interested in point predictions, but also in probabilisti…