… manifold learning algorithm, low rank alignment (LRA), which builds on the ideas of manifold
alignment and LRE to align … novel algorithm for manifold alignment that can align data sets …

… Image alignment consists of … the alignment problem as a manifold distance minimization
problem in the linear subspace defined by the measurements. The transformation manifold that …

… well with perceptual alignment. Finally, based on the levels of on-and off-manifold robustness,
we identify three different regimes of robustness that affect both perceptual alignment and …

… that the mixing efficiency can be dramatically improved by designing a sequentially aligned
mixing structure incorporating H-CMM and a vertically crossing manifold micromixer (V-CMM…

… We propose a manifold alignment based approach for heterogeneous … manifold alignment
approaches by making use of labels rather than correspondences to align the manifolds. This …

… Aligning Local Linear Models Above, we defined a density model for data sampled from
nonlinear manifolds… a global parameterization of the manifold by aligning the local linear models…

… of MixUp, where the mixing policies are automatically learned from the data using an
additional network and objective function designed to avoid manifold intrusion. The proposed …

… than one of the standard linear mixing models. Additionally, we demonstrate … manifold is
then obtained by merging the tile manifolds. We discuss several methods of aligning manifolds …

… attentional manifold alignment (PAMA) to align the content manifold to the style manifold.
The … (b) but renders with uniform and mixed style patterns. In the first row of Fig.8 (e), the blue …

… We present a new algorithm for manifold … the manifold is learned by constructing an
approximation for the tangent space at each data point, and those tangent spaces are then aligned to …