Unsupervised visualization of image datasets using contrastive learning

Unsupervised visualization of image datasets using contrastive learning

18 October 2022

Papers citing "Unsupervised visualization of image datasets using contrastive learning"

15 / 15 papers shown

Title
An Empirically Grounded Identifiability Theory Will Accelerate Self-Supervised Learning Research Patrik Reizinger Randall Balestriero David Klindt Wieland Brendel 40 0 0 17 Apr 2025
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
Dimension Reduction with Locally Adjusted Graphs Yingfan Wang Yiyang Sun Haiyang Huang Cynthia Rudin 80 1 0 19 Dec 2024
Navigating the Effect of Parametrization for Dimensionality Reduction Haiyang Huang Yingfan Wang Cynthia Rudin 79 1 0 24 Nov 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
AEye: A Visualization Tool for Image Datasets Florian Grötschla Luca A. Lanzendörfer Marco Calzavara Roger Wattenhofer 19 1 0 07 Aug 2024
Examining Changes in Internal Representations of Continual Learning Models Through Tensor Decomposition Nishant Suresh Aswani Amira Guesmi Muhammad Abdullah Hanif Muhammad Shafique CLL 22 1 0 06 May 2024
Self-supervised Visualisation of Medical Image Datasets I. V. Nwabufo Jan Niklas Böhm Philipp Berens D. Kobak 42 0 0 22 Feb 2024
Geometric Autoencoders -- What You See is What You Decode Philipp Nazari Sebastian Damrich Fred Hamprecht 30 12 0 30 Jun 2023
Unraveling Projection Heads in Contrastive Learning: Insights from Expansion and Shrinkage Yu Gui Cong Ma Yiqiao Zhong 22 6 0 06 Jun 2023
From $t$ -SNE to UMAP with contrastive learning Sebastian Damrich Jan Niklas Böhm Fred Hamprecht D. Kobak SSL 34 19 0 03 Jun 2022
Your Contrastive Learning Is Secretly Doing Stochastic Neighbor Embedding Tianyang Hu Zhili Liu Fengwei Zhou Wenjia Wang Weiran Huang SSL 39 26 0 30 May 2022
Understanding Deep Contrastive Learning via Coordinate-wise Optimization Yuandong Tian 52 34 0 29 Jan 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
ImageNet Large Scale Visual Recognition Challenge Olga Russakovsky Jia Deng Hao Su J. Krause S. Satheesh ... A. Karpathy A. Khosla Michael S. Bernstein Alexander C. Berg Li Fei-Fei VLM ObjD 296 39,194 0 01 Sep 2014