84 citations · 325 across the 22 of their papers we have counts for
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cs.LG2024
Modeling Human Responses by Ordinal Archetypal Analysis
Anna Emilie J. Wedenborg, Michael Alexander Harborg, Andreas Bigom +6
This paper introduces a novel framework for Archetypal Analysis (AA) tailored to ordinal data, particularly from questionnaires. Unlike existing methods, the proposed method, Ordin…
cs.LG2024
FreqRISE: Explaining time series using frequency masking
Thea Brüsch, Kristoffer Knutsen Wickstrøm, Mikkel N. Schmidt +2
Time-series data are fundamentally important for many critical domains such as healthcare, finance, and climate, where explainable models are necessary for safe automated decision…