Results 11 to 20 of about 5,853,511 (292)
Multi-view manifold learning of human brain-state trajectories. [PDF]
Nat Comput Sci, 2023 Busch EL +7 more
europepmc +2 more sources
Unsupervised manifold learning of collective behavior. [PDF]
PLoS Computational Biology, 2021 Collective behavior is an emergent property of numerous complex systems, from financial markets to cancer cells to predator-prey ecological systems. Characterizing modes of collective behavior is often done through human observation, training generative ...
Mathew Titus +2 more
doaj +2 more sources
Manifold learning in atomistic simulations: a conceptual review [PDF]
Machine Learning: Science and Technology, 2023 Analyzing large volumes of high-dimensional data requires dimensionality reduction: finding meaningful low-dimensional structures hidden in their high-dimensional observations.
J. Rydzewski, Ming Chen, O. Valsson
semanticscholar +1 more source
Manifold Learning with Sparse Regularised Optimal Transport [PDF]
arXiv.org, 2023 Manifold learning is a central task in modern statistics and data science. Many datasets (cells, documents, images, molecules) can be represented as point clouds embedded in a high dimensional ambient space, however the degrees of freedom intrinsic to ...
Stephen X. Zhang +3 more
semanticscholar +1 more source
Pareto Manifold Learning: Tackling multiple tasks via ensembles of single-task models [PDF]
International Conference on Machine Learning, 2022 In Multi-Task Learning (MTL), tasks may compete and limit the performance achieved on each other, rather than guiding the optimization to a solution, superior to all its single-task trained counterparts. Since there is often not a unique solution optimal
Nikolaos Dimitriadis +2 more
semanticscholar +1 more source
IEEE Access, 2021 In recent years, a variety of supervised manifold learning techniques have been proposed to outperform their unsupervised alternative versions in terms of classification accuracy and data structure capturing. Some dissimilarity measures have been used in
Laureta Hajderanj +2 more
doaj +1 more source
Manifold Learning for Knowledge Discovery and Intelligent Inverse Design of Photonic Nanostructures: Breaking the Geometric Complexity [PDF]
ACS Photonics, 2021 Here, we present a new approach based on manifold learning for knowledge discovery and inverse design with minimal complexity in photonic nanostructures.
M. Zandehshahvar +5 more
semanticscholar +1 more source
eLife, 2022 Humans vary greatly in their motor learning abilities, yet little is known about the neural mechanisms that underlie this variability. Recent neuroimaging and electrophysiological studies demonstrate that large-scale neural dynamics inhabit a low ...
Corson Areshenkoff +5 more
doaj +1 more source
Curvature-Balanced Feature Manifold Learning for Long-Tailed Classification
Computer Vision and Pattern Recognition, 2023 To address the challenges of long-tailed classification, researchers have proposed several approaches to reduce model bias, most of which assume that classes with few samples are weak classes.
Yanbiao Ma +5 more
semanticscholar +1 more source
Time Series Forecasting Using Manifold Learning [PDF]
Chaos, 2021 We address a three-tier numerical framework based on nonlinear manifold learning for the forecasting of high-dimensional time series, relaxing the "curse of dimensionality" related to the training phase of surrogate/machine learning models.
P. Papaioannou +3 more
semanticscholar +1 more source