Dmitry Kobak
Zitiert von
Zitiert von
The art of using t-SNE for single-cell transcriptomics
D Kobak, P Berens
Nature communications 10 (1), 5416, 2019
Tracking excess mortality across countries during the COVID-19 pandemic with the World Mortality Dataset
A Karlinsky, D Kobak
elife 10, e69336, 2021
Demixed principal component analysis of neural population data
D Kobak, W Brendel, C Constantinidis, CE Feierstein, A Kepecs, ...
elife 5, e10989, 2016
A multimodal cell census and atlas of the mammalian primary motor cortex
Principal manuscript editors, Analysis coordination, ...
Nature 598 (7879), 86-102, 2021
Initialization is critical for preserving global data structure in both t-SNE and UMAP
D Kobak, GC Linderman
Nature biotechnology 39 (2), 156-157, 2021
Phenotypic variation of transcriptomic cell types in mouse motor cortex
F Scala, D Kobak, M Bernabucci, Y Bernaerts, CR Cadwell, JR Castro, ...
Nature 598 (7879), 144-150, 2021
Distributed and mixed information in monosynaptic inputs to dopamine neurons
J Tian, R Huang, JY Cohen, F Osakada, D Kobak, CK Machens, ...
Neuron 91 (6), 1374-1389, 2016
Layer 4 of mouse neocortex differs in cell types and circuit organization between sensory areas
F Scala, D Kobak, S Shan, Y Bernaerts, S Laturnus, CR Cadwell, ...
Nature communications 10 (1), 1-12, 2019
The optimal ridge penalty for real-world high-dimensional data can be zero or negative due to the implicit ridge regularization
D Kobak, J Lomond, B Sanchez
Journal of Machine Learning Research 21 (169), 1-16, 2020
Analytic Pearson residuals for normalization of single-cell RNA-seq UMI data
J Lause, P Berens, D Kobak
Genome biology 22, 1-20, 2021
Excess mortality reveals Covid's true toll in Russia
D Kobak
Significance (Oxford, England) 18 (1), 16, 2021
Attraction-repulsion spectrum in neighbor embeddings
JN Böhm, P Berens, D Kobak
Journal of Machine Learning Research 23 (95), 1-32, 2022
Patch-seq: Past, present, and future
M Lipovsek, C Bardy, CR Cadwell, K Hadley, D Kobak, SJ Tripathy
Journal of Neuroscience 41 (5), 937-946, 2021
Integer percentages as electoral falsification fingerprints
D Kobak, S Shpilkin, MS Pshenichnikov
Statistical fingerprints of electoral fraud?
D Kobak, S Shpilkin, MS Pshenichnikov
Significance 13 (4), 20-23, 2016
Cell type composition and circuit organization of clonally related excitatory neurons in the juvenile mouse neocortex
CR Cadwell, F Scala, PG Fahey, D Kobak, S Mulherkar, FH Sinz, ...
Elife 9, e52951, 2020
Statistical anomalies in 2011-2012 Russian elections revealed by 2D correlation analysis
D Kobak, S Shpilkin, MS Pshenichnikov
arXiv preprint arXiv:1205.0741, 2012
Heavy-tailed kernels reveal a finer cluster structure in t-SNE visualisations
D Kobak, G Linderman, S Steinerberger, Y Kluger, P Berens
Joint European Conference on Machine Learning and Knowledge Discovery in …, 2019
Sparse reduced-rank regression for exploratory visualisation of paired multivariate data
D Kobak, Y Bernaerts, MA Weis, F Scala, AS Tolias, P Berens
Journal of the Royal Statistical Society Series C: Applied Statistics 70 (4 …, 2021
A systematic evaluation of interneuron morphology representations for cell type discrimination
S Laturnus, D Kobak, P Berens
Neuroinformatics 18, 591-609, 2020
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