… We present a novel method of Hierarchical Manifold Learning which … manifolds in a hierarchy
of image patches of increasing granularity, while ensuring consistency between hierarchy …

… We apply hierarchical manifold learning in order to learn the different motions occurring in
a sequence of real-time cardiac MRI, obtaining spatially-varying respiratory and cardiac corre…

… We propose the Hierarchical Flow (HF) model constrained by isometric regularizations for
manifold learning that combines manifold learning goals such as dimensionality reduction, in…

… Theoretical contributions and applications of manifold learning have progressed in tandem,
… to extend traditional manifold-learning methods. The machine-learning community has …

… learning framework [42], [43], hierarchical manifold learning (HML) … First, we present
hierarchical manifold learning for … In this paper, the hierarchical manifold learning is constructed in …

… and saliency integration by manifold learning. The main contribution of … manifold learning
method is used to ensure the locality and compactness of saliency maps from a hierarchical …

… manifolds of possibly of different dimensionalities, it is unlikely that the existing manifold
learning … We therefore introduce a hierarchical manifolds learning framework to discover a …

… manifold of the data. However, the exploration of reliable and efficient manifold learning …
develop the method of hierarchical simplicial manifold learning. This method systematically …

… which would distort the complex hierarchical structure of cell … been proposed to visualize
hierarchical structures in single-… deep learning approach to visualize the complex hierarchical …

… hierarchical decomposition method in HFDE, and proposes the refined composite hierarchical
… In this paper, the recently proposed manifold learning method—discriminant diffusion …