Relating tSNE and UMAP to Classical Dimensionality Reduction

20 June 2023

Papers citing "Relating tSNE and UMAP to Classical Dimensionality Reduction"

6 / 6 papers shown

Title
The Shape of Attraction in UMAP: Exploring the Embedding Forces in Dimensionality Reduction Mohammad Tariqul Islam Jason W. Fleischer 101 0 0 12 Mar 2025
Anomaly Detection in IR Images of PV Modules using Supervised Contrastive Learning Lukas Bommes M. Hoffmann C. Buerhop‐Lutz Tobias Pickel J. Hauch Christoph J. Brabec Andreas K. Maier I. M. Peters 10 31 0 06 Dec 2021
Decoupled Contrastive Learning Chun-Hsiao Yeh Cheng-Yao Hong Yen-Chi Hsu Tyng-Luh Liu Yubei Chen Yann LeCun 171 182 0 13 Oct 2021
Reducing the Covariate Shift by Mirror Samples in Cross Domain Alignment Yin Zhao Minquan Wang Longjun Cai OOD 23 9 0 13 Oct 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 157 300 0 08 Dec 2020
Cold-start Active Learning through Self-supervised Language Modeling Michelle Yuan Hsuan-Tien Lin Jordan L. Boyd-Graber 104 180 0 19 Oct 2020