Bi-stochastically normalized graph Laplacian: convergence to manifold Laplacian and robustness to outlier noise is a research paper published in Information and Inference A Journal of the IMA (2024). On theSindex it has a DataRank of 0. It has been cited 1 time.
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US National Science Foundation
Grant: DMS-2007040
US National Institutes of Health
Grant: R01GM131642
NSF
Grant: DMS-2237842
Simons Foundation
Grant: 814643
National Science Foundation
Grant: 2007040
NSF-BSF: Group Invariant Graph Laplacians: Theory and Computations
National Science Foundation
Grant: 1820827
CDS&E: Structure-Aware Representation Learning Using Deep Networks
National Science Foundation
Grant: 1818945
Collaborative Research: Geometric Analysis and Computation for Generative Models
National Institutes of Health
Grant: 5R01GM131642-04
EFFICIENT METHODS FOR CALIBRATION, CLUSTERING, VISUALIZATION AND IMPUTATION OF LARGE scRNA-seq DATA
National Science Foundation
Grant: 2134037
Bridging Statistical Hypothesis Tests and Deep Learning for Reliability and Computational Efficiency
FWCI
0.25
Citation Percentile
0.6%
Citation Trend
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