5 citations · 6 across the 5 of their papers we have counts for
8 papers
Temporal Feature Extractors in EEG Foundation Models: A Controlled Comparison Including a Pretrained Time-Series Model
Ayşe Betül Yüce, Chris Joey Leffler, Sarun Varghese +2
Electroencephalography (EEG) foundation models aim to learn generalizable representations from large-scale brain recordings. However, the role of temporal feature extractors and wh…
A cost-based multi-layer network approach for the discovery of patient phenotypes
Clara Puga, Uli Niemann, Winfried Schlee +1
Clinical records frequently include assessments of the characteristics of patients, which may include the completion of various questionnaires. These questionnaires provide a varie…
Probabilistic Active Learning for Active Class Selection
Daniel Kottke, Georg Krempl, Marianne Stecklina +6
In machine learning, active class selection (ACS) algorithms aim to actively select a class and ask the oracle to provide an instance for that class to optimize a classifier's perf…
A Framework for Authorial Clustering of Shorter Texts in Latent Semantic Spaces
Rafi Trad, Myra Spiliopoulou
Authorial clustering involves the grouping of documents written by the same author or team of authors without any prior positive examples of an author's writing style or thematic p…
Cardiac Cohort Classification based on Morphologic and Hemodynamic Parameters extracted from 4D PC-MRI Data
Uli Niemann, Atrayee Neog, Benjamin Behrendt +5
An accurate assessment of the cardiovascular system and prediction of cardiovascular diseases (CVDs) are crucial. Measured cardiac blood flow data provide insights about patient-sp…
How Does Tweet Difficulty Affect Labeling Performance of Annotators?
Stefan Räbiger, Yücel Saygın, Myra Spiliopoulou
Crowdsourcing is a popular means to obtain labeled data at moderate costs, for example for tweets, which can then be used in text mining tasks. To alleviate the problem of low-qual…