Sparse Count Data Modeling
Sparse Count Data Modeling is a statistical framework for analyzing high-dimensional count data characterized by an excess of zero values, where the modeling approach specifically accounts for sparsity to enable accurate inference in single-cell genomic measurements.
28
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3.1K
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77
Authors
54
Institutions
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2017–2026
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28
Single-cell RNA-seq denoising using a deep count autoencoder
Gökçen Eraslan, Lukas M. Simon, Maria Mircea et al. · Nature Communications · 2019 · 1.2K citations · Full text
On Smoothing and Inference for Topic Models
Arthur Asuncion, Max Welling, Padhraic Smyth et al. · arXiv (Cornell University) · 2012 · 452 citations · Full text
Pascal Monestiez, Laurent Dubroca, Emilie Bonnin et al. · Ecological Modelling · 2005 · 155 citations
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University of Minnesota
Minneapolis, United States
3 h-index
3 publications
188 citations
University of Florida
Gainesville, United States
2 h-index
3 publications
301 citations

Helmholtz Zentrum München
Munich, Germany
2 h-index
9 publications
6.1K citations
Technical University of Munich
Munich, Germany
2 h-index
4 publications
2.5K citations
Harvard University
Cambridge, United States
2 h-index
2 publications
162 citations

Harvard University Press
Cambridge, United States
1 h-index
1 publications
146 citations

Aarhus University
Aarhus, Denmark
1 h-index
1 publications
12 citations

University of Louisville
Louisville, United States
1 h-index
2 publications
30 citations
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Repository · 3 publications · 492 citations
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3 publications · 189 citations
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Repository · 2 publications · 115 citations
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1 publications · 79 citations
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1 publications · 282 citations
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