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ORCIDDmitry Kobak
Person information
- affiliation: University of Tübingen, Germany
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Journal Articles
- 2024
[j5]Rita González-Márquez, Luca Schmidt, Benjamin M. Schmidt, Philipp Berens, Dmitry Kobak
:
The landscape of biomedical research. Patterns 5(6): 100968 (2024)- [j4]Rita González-Márquez, Philipp Berens, Dmitry Kobak:
Meet the authors: Rita González-Márquez, Philipp Berens, and Dmitry Kobak. Patterns 5(6): 100993 (2024) - 2022
- [j3]Jan Niklas Böhm, Philipp Berens, Dmitry Kobak:
Attraction-Repulsion Spectrum in Neighbor Embeddings. J. Mach. Learn. Res. 23: 95:1-95:32 (2022) - 2020
- [j2]Dmitry Kobak, Jonathan Lomond, Benoit Sanchez:
The Optimal Ridge Penalty for Real-world High-dimensional Data Can Be Zero or Negative due to the Implicit Ridge Regularization. J. Mach. Learn. Res. 21: 169:1-169:16 (2020) - [j1]Sophie Laturnus, Dmitry Kobak, Philipp Berens:
A Systematic Evaluation of Interneuron Morphology Representations for Cell Type Discrimination. Neuroinformatics 18(4): 591-609 (2020)
Conference and Workshop Papers
- 2024
- [c8]Samuel Greydanus, Dmitry Kobak:
Scaling Down Deep Learning with MNIST-1D. ICML 2024 - 2023
- [c7]Jan Niklas Böhm, Philipp Berens, Dmitry Kobak:
Unsupervised visualization of image datasets using contrastive learning. ICLR 2023 - [c6]Sebastian Damrich, Jan Niklas Böhm, Fred A. Hamprecht, Dmitry Kobak:
From $t$-SNE to UMAP with contrastive learning. ICLR 2023 - 2022
- [c5]Gaik Tamazian, Andrey B. Komissarov, Dmitry Kobak, Dmitry Polyakov, Evgeny Andronov, Sergei Nechaev, Sergey Kryzhevich, Yuri Porozov, Eugene Stepanov:
t-SNE Highlights Phylogenetic and Temporal Patterns of SARS-CoV-2 Spike and Nucleocapsid Protein Evolution. ISBRA 2022: 255-262 - [c4]Fynn Bachmann, Philipp Hennig, Dmitry Kobak:
Wasserstein t-SNE. ECML/PKDD (1) 2022: 104-120 - [c3]Rita González-Márquez, Philipp Berens, Dmitry Kobak:
Two-dimensional visualization of large document libraries using t-SNE. TAG-ML 2022: 133-141 - 2021
- [c2]Indu Ilanchezian, Dmitry Kobak, Hanna Faber, Focke Ziemssen, Philipp Berens, Murat Seçkin Ayhan:
Interpretable Gender Classification from Retinal Fundus Images Using BagNets. MICCAI (3) 2021: 477-487 - 2019
- [c1]Dmitry Kobak, George C. Linderman, Stefan Steinerberger, Yuval Kluger, Philipp Berens:
Heavy-Tailed Kernels Reveal a Finer Cluster Structure in t-SNE Visualisations. ECML/PKDD (1) 2019: 124-139
Informal and Other Publications
- 2024
- [i11]Ifeoma Veronica Nwabufo, Jan Niklas Böhm, Philipp Berens, Dmitry Kobak:
Self-supervised Visualisation of Medical Image Datasets. CoRR abs/2402.14566 (2024) - [i10]Rita González-Márquez, Dmitry Kobak:
Learning representations of learning representations. CoRR abs/2404.08403 (2024) - [i9]Dmitry Kobak, Rita González-Márquez, Emoke-Ágnes Horvát, Jan Lause:
Delving into ChatGPT usage in academic writing through excess vocabulary. CoRR abs/2406.07016 (2024) - [i8]Dmitry Kobak, Fred A. Hamprecht, Smita Krishnaswamy, Gal Mishne, Sebastian Damrich:
Low-Dimensional Embeddings of High-Dimensional Data: Algorithms and Applications (Dagstuhl Seminar 24122). Dagstuhl Reports 14(3): 92-115 (2024) - 2023
- [i7]Sebastian Damrich, Philipp Berens, Dmitry Kobak:
Persistent homology for high-dimensional data based on spectral methods. CoRR abs/2311.03087 (2023) - 2022
- [i6]Fynn Bachmann, Philipp Hennig, Dmitry Kobak:
Wasserstein t-SNE. CoRR abs/2205.07531 (2022) - [i5]Sebastian Damrich, Jan Niklas Böhm, Fred A. Hamprecht, Dmitry Kobak:
Contrastive learning unifies t-SNE and UMAP. CoRR abs/2206.01816 (2022) - [i4]Jan Niklas Böhm, Philipp Berens, Dmitry Kobak:
Unsupervised visualization of image datasets using contrastive learning. CoRR abs/2210.09879 (2022) - 2020
- [i3]Yves Bernaerts, Philipp Berens, Dmitry Kobak:
Sparse Bottleneck Networks for Exploratory Analysis and Visualization of Neural Patch-seq Data. CoRR abs/2006.10411 (2020) - [i2]Jan Niklas Böhm, Philipp Berens, Dmitry Kobak:
A Unifying Perspective on Neighbor Embeddings along the Attraction-Repulsion Spectrum. CoRR abs/2007.08902 (2020) - 2019
- [i1]Dmitry Kobak, George C. Linderman, Stefan Steinerberger, Yuval Kluger, Philipp Berens:
Heavy-tailed kernels reveal a finer cluster structure in t-SNE visualisations. CoRR abs/1902.05804 (2019)
Coauthor Index
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