Dmitry Kobak
Title
Cited by
Cited by
Year
Demixed principal component analysis of neural population data
D Kobak, W Brendel, C Constantinidis, CE Feierstein, A Kepecs, ...
Elife 5, e10989, 2016
2622016
The art of using t-SNE for single-cell transcriptomics
D Kobak, P Berens
Nature communications 10 (1), 1-14, 2019
2122019
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
1582016
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
47*2019
Phenotypic variation of transcriptomic cell types in mouse motor cortex
F Scala, D Kobak, M Bernabucci, Y Bernaerts, CR Cadwell, JR Castro, ...
Nature, 1-7, 2020
40*2020
Statistical fingerprints of electoral fraud?
D Kobak, S Shpilkin, MS Pshenichnikov
Significance 13 (4), 20-23, 2016
40*2016
Integer percentages as electoral falsification fingerprints
D Kobak, S Shpilkin, MS Pshenichnikov
The Annals of Applied Statistics 10 (1), 54-73, 2016
402016
Statistical anomalies in 2011-2012 Russian elections revealed by 2D correlation analysis
D Kobak, S Shpilkin, MS Pshenichnikov
arXiv preprint arXiv:1205.0741, 2012
392012
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
33*2021
Tracking excess mortality across countries during the COVID-19 pandemic with the World Mortality Dataset
A Karlinsky, D Kobak
eLife 10, e69336, 2021
26*2021
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
26*2020
Adaptation paths to novel motor tasks are shaped by prior structure learning
D Kobak, C Mehring
Journal of Neuroscience 32 (29), 9898-9908, 2012
202012
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
13*2020
A multimodal cell census and atlas of the mammalian primary motor cortex
RS Adkins, AI Aldridge, S Allen, SA Ament, X An, E Armand, GA Ascoli, ...
BioRxiv, 2020
112020
Heavy-tailed kernels reveal a finer cluster structure in t-SNE visualisations
D Kobak, G Linderman, S Steinerberger, Y Kluger, P Berens
Machine learning and knowledge discovery in databases: European Conference …, 2020
112020
A systematic evaluation of interneuron morphology representations for cell type discrimination
S Laturnus, D Kobak, P Berens
Neuroinformatics 18 (4), 591-609, 2020
92020
Excess mortality reveals Covid's true toll in Russia
D Kobak
Significance (Oxford, England) 18 (1), 16, 2021
82021
Putin's peaks: Russian election data revisited
D Kobak, S Shpilkin, MS Pshenichnikov
Significance 15 (3), 8-9, 2018
82018
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), 2021
7*2021
A unifying perspective on neighbor embeddings along the attraction-repulsion spectrum
JN Böhm, P Berens, D Kobak
arXiv preprint arXiv:2007.08902, 2020
62020
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Articles 1–20