Miroslav Kratochvı́l

2019

A researcher in the Science corpus: 1 paper; trusts 1 researcher and is trusted by 0 researchers here, as inferred from the citation graph.

Whom Miroslav Kratochvı́l trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. L. V. D. van der Maaten
2. Leland McInnes
3. Jiarui Ding
4. Nicola Pezzotti
5. S. van Gassen
6. John Healy
7. George C. Linderman
8. Anna C. Belkina
9. Etienne Becht

Papers from Miroslav Kratochvı́l's perspective

Ordered by how strongly the researchers Miroslav Kratochvı́l trusts endorse each paper. Same corpus, a different order for every researcher.

1. Accelerating t-SNE using tree-based algorithms
2. UMAP: Uniform Manifold Approximation and Projection for Dimension Reduction
3. Computational flow cytometry: helping to make sense of high-dimensional immunology data (Nature reviews. Immunology)
4. Visualizing Data using t-SNE
5. Gradient-based learning applied to document recognition
6. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
7. Data-driven phenotypic dissection of AML reveals progenitor-like cells that correlate with prognosis
8. ImageNet classification with deep convolutional neural networks
9. Approximated and User Steerable tSNE for Progressive Visual Analytics
10. Dimensionality reduction for visualizing single-cell data using UMAP

Their papers

• SOM-based embedding improves efficiency of high-dimensional cytometry data analysis (2019)