Regularization of Mixture Models for Robust Principal Graph Learning
Sign Up to like & getrecommendations! Published in 2021 at "IEEE transactions on pattern analysis and machine intelligence"
DOI: 10.1109/tpami.2021.3124973
Abstract: A regularized version of Mixture Models is proposed to learn a principal graph from a distribution of D-dimensional data points. In the particular case of manifold learning for ridge detection, we assume that the underlying… read more here.
Keywords: mixture models; principal graph; graph; regularization mixture ... See more keywords
Geometric models for robust encoding of dynamical information into embryonic patterns
Sign Up to like & getrecommendations! Published in 2020 at "eLife"
DOI: 10.7554/elife.55778
Abstract: During development, cells gradually assume specialized fates via changes of transcriptional dynamics, sometimes even within the same developmental stage. For anterior-posterior (AP) patterning in metazoans, it has been suggested that the gradual transition from a… read more here.
Keywords: robust encoding; dynamical information; geometric models; patterns geometric ... See more keywords