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stat.ML2024
Fast Empirical Scenarios
Michael Multerer, Paul Schneider, Rohan Sen
We seek to extract a small number of representative scenarios from large panel data that are consistent with sample moments. Among two novel algorithms, the first identifies scenar…
stat.ML2024
Adaptive joint distribution learning
Damir Filipovic, Michael Multerer, Paul Schneider
We develop a new framework for estimating joint probability distributions using tensor product reproducing kernel Hilbert spaces (RKHS). Our framework accommodates a low-dimensiona…
stat.ML2024
Observation-specific explanations through scattered data approximation
Valentina Ghidini, Michael Multerer, Jacopo Quizi +1
This work introduces the definition of observation-specific explanations to assign a score to each data point proportional to its importance in the definition of the prediction pro…