Attraction-Repulsion Spectrum in Neighbor Embeddings

17 July 2020

Papers citing "Attraction-Repulsion Spectrum in Neighbor Embeddings"

27 / 27 papers shown

Title
Node Embeddings via Neighbor Embeddings Jan Niklas Böhm Marius Keute Alica Guzmán Sebastian Damrich Andrew Draganov D. Kobak GNN 57 0 0 31 Mar 2025
The Shape of Attraction in UMAP: Exploring the Embedding Forces in Dimensionality Reduction Mohammad Tariqul Islam Jason W. Fleischer 166 0 0 12 Mar 2025
Navigating the Effect of Parametrization for Dimensionality Reduction Haiyang Huang Yingfan Wang Cynthia Rudin 81 1 0 24 Nov 2024
Large data limits and scaling laws for tSNE Ryan Murray Adam Pickarski 18 1 0 16 Oct 2024
FedNE: Surrogate-Assisted Federated Neighbor Embedding for Dimensionality Reduction Ziwei Li Xiaoqi Wang Hong-You Chen Han-Wei Shen Wei-Lun Chao FedML 32 0 0 17 Sep 2024
Outlier Detection in Large Radiological Datasets using UMAP Mohammad Tariqul Islam Jason W. Fleischer 48 1 0 31 Jul 2024
Sailing in high-dimensional spaces: Low-dimensional embeddings through angle preservation Jonas Fischer Rong Ma 51 0 0 14 Jun 2024
Re-visiting Skip-Gram Negative Sampling: Dimension Regularization for More Efficient Dissimilarity Preservation in Graph Embeddings David Liu Arjun Seshadri Tina Eliassi-Rad J. Ugander 26 1 0 30 Apr 2024
Graph Vertex Embeddings: Distance, Regularization and Community Detection Radoslaw Nowak Adam Malkowski Daniel Cie'slak Piotr Sokól Pawel Wawrzyñski 23 0 0 09 Apr 2024
Curvature Augmented Manifold Embedding and Learning Yongming Liu MedIm 116 2 0 21 Mar 2024
Convergence analysis of t-SNE as a gradient flow for point cloud on a manifold Seonghyeon Jeong Hau-tieng Wu 15 2 0 31 Jan 2024
Accelerating hyperbolic t-SNE Martin Skrodzki Hunter van Geffen Nicolas F. Chaves-de-Plaza T. Höllt E. Eisemann Klaus Hildebrandt 36 3 0 23 Jan 2024
Manifold learning: what, how, and why M. Meilă Hanyu Zhang 15 55 0 07 Nov 2023
Persistent Homology for High-dimensional Data Based on Spectral Methods Sebastian Damrich Philipp Berens D. Kobak 17 2 0 06 Nov 2023
Supervised Stochastic Neighbor Embedding Using Contrastive Learning Yi Zhang SSL 11 0 0 15 Sep 2023
Class-constrained t-SNE: Combining Data Features and Class Probabilities Linhao Meng S. V. D. Elzen Nicola Pezzotti Anna Vilanova 21 10 0 26 Aug 2023
Relating tSNE and UMAP to Classical Dimensionality Reduction Andrew Draganov Simon Dohn FAtt 27 4 0 20 Jun 2023
Efficient and Robust Bayesian Selection of Hyperparameters in Dimension Reduction for Visualization Yin-Ting Liao Hengrui Luo A. Ma 13 3 0 01 Jun 2023
A Heat Diffusion Perspective on Geodesic Preserving Dimensionality Reduction G. Huguet Alexander Tong E. Brouwer Yanlei Zhang Guy Wolf Ian M. Adelstein Smita Krishnaswamy DiffM 20 7 0 30 May 2023
Collection Space Navigator: An Interactive Visualization Interface for Multidimensional Datasets Tillmann Ohm M. Sola Andres Karjus Maximilian Schich 24 6 0 11 May 2023
Interpretable Dimensionality Reduction by Feature Preserving Manifold Approximation and Projection Yang Yang Hongjian Sun Jialei Gong Di Yu FAtt 34 2 0 17 Nov 2022
Unsupervised visualization of image datasets using contrastive learning Jan Boehm Philipp Berens D. Kobak SSL 26 15 0 18 Oct 2022
ParaDime: A Framework for Parametric Dimensionality Reduction A. Hinterreiter Christina Humer Bernhard Kainz M. Streit 30 5 0 10 Oct 2022
On the Selection of Tuning Parameters for Patch-Stitching Embedding Methods E. Arias-Castro Phong Alain Chau 17 0 0 14 Jul 2022
From $t$ -SNE to UMAP with contrastive learning Sebastian Damrich Jan Niklas Böhm Fred Hamprecht D. Kobak SSL 48 19 0 03 Jun 2022
Visualizing hierarchies in scRNA-seq data using a density tree-biased autoencoder Q. Garrido Sebastian Damrich Alexander Jäger Dario Cerletti Manfred Claassen Laurent Najman Fred Hamprecht 17 5 0 11 Feb 2021
Measuring and testing dependence by correlation of distances G. Székely Maria L. Rizzo N. K. Bakirov 179 2,578 0 28 Mar 2008