From $t$-SNE to UMAP with contrastive learning

From $t$ -SNE to UMAP with contrastive learning

3 June 2022

Sebastian Damrich

Jan Niklas Böhm

Papers citing "From $t$-SNE to UMAP with contrastive learning"

11 / 11 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 157 0 0 12 Mar 2025
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
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
Towards One Model for Classical Dimensionality Reduction: A Probabilistic Perspective on UMAP and t-SNE Aditya Ravuri Neil D. Lawrence 28 1 0 27 May 2024
Improving neural network representations using human similarity judgments Lukas Muttenthaler Lorenz Linhardt Jonas Dippel Robert A. Vandermeulen Katherine L. Hermann Andrew Kyle Lampinen Simon Kornblith 40 29 0 07 Jun 2023
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 25 5 0 10 Oct 2022
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 159 301 0 08 Dec 2020
Contrastive Representation Learning: A Framework and Review Phúc H. Lê Khắc Graham Healy Alan F. Smeaton SSL AI4TS 175 685 0 10 Oct 2020
Bringing UMAP Closer to the Speed of Light with GPU Acceleration Corey J. Nolet V. Lafargue Edward Raff Thejaswi Nanditale Tim Oates John Zedlewski Joshua Patterson 34 33 0 01 Aug 2020