3 papers
cs.LG2026
Scalable Learning of Multivariate Distributions via Coresets
Zeyu Ding, Katja Ickstadt, Nadja Klein +2
Efficient and scalable non-parametric or semi-parametric regression analysis and density estimation are of crucial importance to the fields of statistics and machine learning. Howe…
stat.ME2026
Guidance for Addressing Individual Time Effects in Cohort Stepped Wedge Cluster Randomized Trials: A Simulation Study
Jale Basten, Katja Ickstadt, Nina Timmesfeld
Background: Stepped wedge cluster randomized trials (SW-CRTs) involve sequential measurements within clusters over time. Initially, all clusters start in the control condition befo…
stat.CO2025
MCBench: A Benchmark Suite for Monte Carlo Sampling Algorithms
Zeyu Ding, Cornelius Grunwald, Katja Ickstadt +2
In this paper, we present MCBench, a benchmark suite designed to assess the quality of Monte Carlo (MC) samples. The benchmark suite enables quantitative comparisons of samples by…