1 citations · 3 across the 3 of their papers we have counts for
Showing stat.MLShow all
2 papers · 1 filter
stat.ML2023★ 1 cited
Multi-view self-supervised learning for multivariate variable-channel time series
Thea Brüsch, Mikkel N. Schmidt, Tommy S. Alstrøm
Labeling of multivariate biomedical time series data is a laborious and expensive process. Self-supervised contrastive learning alleviates the need for large, labeled datasets thro…
stat.ML2014★ 1 cited
Adaptive Reconfiguration Moves for Dirichlet Mixtures
Tue Herlau, Morten Mørup, Yee Whye Teh +1
Bayesian mixture models are widely applied for unsupervised learning and exploratory data analysis. Markov chain Monte Carlo based on Gibbs sampling and split-merge moves are widel…