Many high-dimensional data sets that lie on a low- dimensional manifold exhibit nontrivial regularities at mul- tiple scales. Most work in manifold learning ...
Mar 27, 2023 · PHATE is a diffusion-based manifold learning method that models local and global structures simultaneously in nonlinear dimensions. Brain ...
In this paper, we show that exploiting the multiscale manifold latent structure of real-world data can yield improved alignment. We introduce a ...
Mar 8, 2023 · Multiscale Manifold Learning. March 8, 2023. Authors. Chang Wang. IBM Research. Sridhar Mahadevan. University of Massachusetts. Proceedings: No.
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We describe an efficient domain decomposition-based framework for nonlinear multiscale PDE problems. The framework is inspired by manifold learning ...
Apr 19, 2023 · Generically, a multiscale setup requires two fundamental building blocks: (a) the ability to define relevant scales and bridge them locally, ...
Missing: Manifold | Show results with:Manifold
Feb 7, 2022 · The method aims to improve the performance of manifold learning for multiple tasks, particularly when each task has a small number of samples.
Oct 31, 2022 · In this work, we propose a framework to study the geometric structure of the data. We make use of our recently introduced non-negative kernel ( ...
In this paper, we propose a novel Gen- eralized Clustering and Multi-manifold Learning (GCML) framework with geometric structure preservation for gener- alized ...
Nov 25, 2019 · Multiscale modeling integrates the underlying physics towards identifying relevant features, exploring their interaction, elucidating mechanisms ...
Missing: Manifold | Show results with:Manifold