Heavy-tailed kernels reveal a finer cluster structure in t-SNE visualisations

15 February 2019

Papers citing "Heavy-tailed kernels reveal a finer cluster structure in t-SNE visualisations"

7 / 7 papers shown

Title
Random Forest Autoencoders for Guided Representation Learning Adrien Aumon Shuang Ni Myriam Lizotte Guy Wolf Kevin R. Moon Jake S. Rhodes 67 0 0 18 Feb 2025
Preserving local densities in low-dimensional embeddings Jonas Fischer R. Burkholz Jilles Vreeken 27 3 0 31 Jan 2023
A Probabilistic Graph Coupling View of Dimension Reduction Hugues van Assel T. Espinasse J. Chiquet F. Picard 19 14 0 31 Jan 2022
Topological Indoor Mapping through WiFi Signals Bastian Schaefermeier Gerd Stumme Tom Hanika 21 0 0 17 Jun 2021
Understanding How Dimension Reduction Tools Work: An Empirical Approach to Deciphering t-SNE, UMAP, TriMAP, and PaCMAP for Data Visualization Yingfan Wang Haiyang Huang Cynthia Rudin Yaron Shaposhnik 164 304 0 08 Dec 2020
Attraction-Repulsion Spectrum in Neighbor Embeddings Jan Niklas Böhm Philipp Berens D. Kobak 34 53 0 17 Jul 2020
Visualizing the Finer Cluster Structure of Large-Scale and High-Dimensional Data Yuefeng Liang A. Chaudhuri Haoyu Wang 18 0 0 17 Jul 2020