Results 31 to 40 of about 1,708,415 (229)

Schematic overview of the nonnegative matrix factorization (NMF) algorithm.

, 2023
Schematic overview of the nonnegative matrix factorization (NMF) algorithm.
Chaur-Jong Hu (125228), Chih-Yang Yeh (6736199), Truc Tran Thanh Nguyen (17102808), Hsun-Hua Lee (5466971), Li-Kai Huang (9513864), Wei-Chung Vivian Yang (2063686), Ming-Chin Lin (6736202)   +6 more
core   +1 more source

Early Spatial and Contextual Coding Deficits in Hippocampal CA1 Precede Performance Decline in an Alzheimer's Disease Model

Advanced Science, EarlyView.
Two‐photon calcium imaging in behaving 5xFAD mice reveals early CA1 coding deficits before behavioral decline. Task‐related place cell activity and splitter cell trajectory coding are impaired, with reduced retrospective dominance and greater prospective weighting.
Yimei Li, Mary Ann Go, Hualong Zhang, Robertas Aleksynas, Juliana Kim, Mingyang Gao, Seigfred Prado, Magdalena Sastre, Simon R. Schultz   +8 more
wiley   +1 more source

Adaptive Graph Regularization Discriminant Nonnegative Matrix Factorization for Data Representation

IEEE Access, 2019
Nonnegative matrix factorization, as a classical part-based representation method, has been widely used in pattern recognition, data mining and other fields.
Lin Zhang, Zhonghua Liu, Lin Wang, Jiexin Pu   +3 more
doaj   +1 more source

On the Probabilistic Latent Semantic Analysis Generalization as the Singular Value Decomposition Probabilistic Image

Journal of Statistical Theory and Applications (JSTA), 2020
The Probabilistic Latent Semantic Analysis has been related with the Singular Value Decomposition. Several problems occur when this comparative is done.
Pau Figuera Vinué, Pablo García Bringas   +1 more
doaj   +1 more source

Reverse annealing for nonnegative/binary matrix factorization.

PLoS ONE, 2021
It was recently shown that quantum annealing can be used as an effective, fast subroutine in certain types of matrix factorization algorithms. The quantum annealing algorithm performed best for quick, approximate answers, but performance rapidly ...
John Golden, Daniel O'Malley
doaj   +1 more source

Towards a Compositional Framework for Describing Human Phenotypes

Advanced Science, EarlyView.
The Phenotype Assembly Method (PhenoAM) decomposes phenotype variables into measurable Features and typed Qualifiers, enabling standardized, machine‐readable Phenome Data Elements (PhenoDEs) that preserve measurement context. Applied in the International Human Phenome Project (IHPP), the framework yields 58 371 PhenoDEs and supports component‐level ...
Wanting Hu, Yunchao Ling, Xinyue Hu, Wei Chen, Rong Zhou, Xinhao Zhuang, Yanfeng Jiang, Jialu Zhao, Xingdong Chen, Jingchun Luo, Li Jin, Guoqing Zhang   +11 more
wiley   +1 more source

Optimization of identifiability for efficient community detection

New Journal of Physics, 2020
Many physical and social systems are best described by networks. And the structural properties of these networks often critically determine the properties and function of the resulting mathematical models.
Hui-Jia Li, Lin Wang, Yan Zhang, Matjaž Perc   +3 more
doaj   +1 more source

Integrated Multi‐Omics Reveals Cellular States and Microenvironmental Remodeling in Coexisting DCIS and IDC

Advanced Science, EarlyView.
Coexisting DCIS and IDC samples are profiled using spatial transcriptomics, single‐cell RNA sequencing, and single‐cell DNA sequencing. Integrative multi‐omics analysis reveals distinct malignant epithelial and microenvironmental features between DCIS and IDC, which are further validated using Xenium and multiplex immunohistochemistry.
Ning Zhang, Tong Wan, Siyue Zhang, Yunzhen Jiang, Peng Su, Jixin Liu, Zhitong Chen, Jie Hao, Haoyu Wang, Bing Chen, Wenjing Zhao, Lijuan Wang, Tao Xing, Qihuang Zhang, Ulf Schmitz, Zhiyong Ding, Nicola Crosetto, Bingqiang Liu, Qifeng Yang   +18 more
wiley   +1 more source

Spectro-temporal post-enhancement using MMSE estimation in NMF based single-channel source separation [PDF]

, 2013
We propose to use minimum mean squared error (MMSE) estimates to enhance the signals that are separated by nonnegative matrix factorization (NMF). In single channel source separation (SCSS), NMF is used to train a set of basis vectors for each source ...
Erdoğan, Hakan, Grais, Emad Mounir, Hakan Erdogan, Emad M. Grais   +3 more
core   +1 more source

Multiple Graph Adaptive Regularized Semi-Supervised Nonnegative Matrix Factorization with Sparse Constraint for Data Representation

, 2022
Multiple graph and semi-supervision techniques have been successfully introduced into the nonnegative matrix factorization (NMF) model for taking full advantage of the manifold structure and priori information of data to capture excellent low-dimensional
Yi Wang, Wang, Yi, Zhao, Xuezhuan, Lingling Li, Zhang, Ji, Di, Jinhong, Kexin Zhang, Jinhong Di, Xuezhuan Zhao, Zhang, Kexin, Ji Zhang, Li, Lingling   +11 more
core   +1 more source