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Python Source Code - 301.6 KB - MD5: 14d67a43ed760cab8072b5bb385ab74b
PNG Image - 5.5 KB - MD5: 54863785c35b3c8de1eea421f4eb1be8
training stimulus
PNG Image - 5.5 KB - MD5: 54863785c35b3c8de1eea421f4eb1be8
Tabular Data - 202 B - 1 Variables, 2 Observations - UNF:6:p1ooQDA8PYvP6ru6/PUj9w==
PNG Image - 3.2 KB - MD5: 1b61443026e1db22917e5c0867ecc308
PNG Image - 3.2 KB - MD5: 1b61443026e1db22917e5c0867ecc308
training stimulus
Tabular Data - 202 B - 1 Variables, 2 Observations - UNF:6:jJdXhs2twUjeiK39RFsBCg==
application/x-msschedule - 8.6 KB - MD5: a36bf9d46731857af2551eed344a4978
Script used to generate sound stimuli. Created in supercollider: https://supercollider.github.io/
Python Source Code - 5.7 KB - MD5: 09a97329bd8c067b7424dbd66e3c57d6
Script used to generate visual stimuli.
Sep 16, 2024
Evers, Marina; Weiskopf, Daniel, 2024, "Supplementary Material for Uncertainty-aware Spectral Visualization", https://doi.org/10.18419/DARUS-4447, DaRUS, V1
In this supplemental material, we provide supplemental information (PDF document with derivations of the results presented in the paper and two additional use cases) and the supplementary video for uncertainty-aware spectral analysis. We model an uncertain time series as a multivariate Gaussian process. We propagate the uncertainty and explicitly c...
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