Visualizing Large-scale and High-dimensional Data

1 February 2016

Jian Tang

Papers citing "Visualizing Large-scale and High-dimensional Data"

50 / 98 papers shown

Title
NOMAD Projection Brandon Duderstadt Zach Nussbaum Laurens van der Maaten AI4TS 12 0 0 21 May 2025
The Shape of Attraction in UMAP: Exploring the Embedding Forces in Dimensionality Reduction Mohammad Tariqul Islam Jason W. Fleischer 247 0 0 12 Mar 2025
Dimension Reduction with Locally Adjusted Graphs Yingfan Wang Yiyang Sun Haiyang Huang Cynthia Rudin 88 1 0 19 Dec 2024
Navigating the Effect of Parametrization for Dimensionality Reduction Haiyang Huang Yingfan Wang Cynthia Rudin 81 1 0 24 Nov 2024
Assessing and improving reliability of neighbor embedding methods: a map-continuity perspective Zhexuan Liu Rong Ma Yiqiao Zhong 62 0 0 22 Oct 2024
MIK: Modified Isolation Kernel for Biological Sequence Visualization, Classification, and Clustering Sarwan Ali Prakash Chourasia Haris Mansoor Bipin Koirala Murray Patterson 213 0 0 21 Oct 2024
G-NeuroDAVIS: A Neural Network model for generalized embedding, data visualization and sample generation Chayan Maitra R. K. De BDL 26 0 0 18 Oct 2024
Nearest Neighbor CCP-Based Molecular Sequence Analysis Sarwan Ali Prakash Chourasia Bipin Koirala Murray Patterson 42 1 0 07 Sep 2024
Out-of-Core Dimensionality Reduction for Large Data via Out-of-Sample Extensions Luca Reichmann David Hägele Daniel Weiskopf 207 0 0 07 Aug 2024
A Unified Framework for Combinatorial Optimization Based on Graph Neural Networks Yaochu Jin Xueming Yan Shiqing Liu Xiangyu Wang 51 3 0 19 Jun 2024
MASSW: A New Dataset and Benchmark Tasks for AI-Assisted Scientific Workflows Xingjian Zhang Yutong Xie Jin Huang Jinge Ma Zhaoying Pan ... Ziyang Xiong Tolga Ergen Dongsub Shim Honglak Lee Qiaozhu Mei 51 10 0 10 Jun 2024
MS-IMAP -- A Multi-Scale Graph Embedding Approach for Interpretable Manifold Learning Shay Deutsch Lionel Yelibi Alex Tong Lin Arjun Ravi Kannan 56 1 0 04 Jun 2024
Curvature Augmented Manifold Embedding and Learning Yongming Liu MedIm 126 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
Scalable manifold learning by uniform landmark sampling and constrained locally linear embedding D. Peng Zhipeng Gui Wenzhang Wei Huayi Wu 40 1 0 02 Jan 2024
k* Distribution: Evaluating the Latent Space of Deep Neural Networks using Local Neighborhood Analysis Shashank Kotyan Tatsuya Ueda Danilo Vasconcellos Vargas 34 1 0 07 Dec 2023
Cluster Exploration using Informative Manifold Projections Stavros Gerolymatos Xenophon Evangelopoulos V. Gusev John Y. Goulermas 19 0 0 26 Sep 2023
Higher-order Motif-based Time Series Classification for Forced Oscillation Source Location in Power Grids L. Huo Xin Chen AI4TS 13 2 0 23 Jun 2023
Relating tSNE and UMAP to Classical Dimensionality Reduction Andrew Draganov Simon Dohn FAtt 32 4 0 20 Jun 2023
WizMap: Scalable Interactive Visualization for Exploring Large Machine Learning Embeddings Zijie J. Wang Fred Hohman Duen Horng Chau 42 21 0 15 Jun 2023
ActUp: Analyzing and Consolidating tSNE and UMAP Andrew Draganov Jakob Rødsgaard Jørgensen Katrine Scheel Nellemann Davide Mottin Ira Assent Tyrus Berry Çigdem Aslay 19 5 0 12 May 2023
Collection Space Navigator: An Interactive Visualization Interface for Multidimensional Datasets Tillmann Ohm M. Sola Andres Karjus Maximilian Schich 27 6 0 11 May 2023
Force-Directed Graph Layouts Revisited: A New Force Based on the T-Distribution Fahai Zhong Mingliang Xue Jian Zhang Fan Zhang Rui Ban Oliver Deussen Yunhai Wang 23 8 0 05 Mar 2023
Backdoor Attacks Against Dataset Distillation Yugeng Liu Zheng Li Michael Backes Yun Shen Yang Zhang DD 47 28 0 03 Jan 2023
EVNet: An Explainable Deep Network for Dimension Reduction Z. Zang Sheng-Hsien Cheng Linyan Lu Hanchen Xia Liangyu Li Yaoting Sun Yongjie Xu Lei Shang Baigui Sun Stan Z. Li FAtt 32 15 0 21 Nov 2022
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
A Complex Network based Graph Embedding Method for Link Prediction Said Kerrache Hafida Benhidour 13 1 0 11 Sep 2022
IAN: Iterated Adaptive Neighborhoods for manifold learning and dimensionality estimation Luciano Dyballa Steven W. Zucker 13 9 0 19 Aug 2022
FibeRed: Fiberwise Dimensionality Reduction of Topologically Complex Data with Vector Bundles Luis Scoccola Jose A. Perea 13 8 0 13 Jun 2022
From $t$ -SNE to UMAP with contrastive learning Sebastian Damrich Jan Niklas Böhm Fred Hamprecht D. Kobak SSL 48 21 0 03 Jun 2022
ENS-t-SNE: Embedding Neighborhoods Simultaneously t-SNE Jacob Miller Vahan Huroyan Raymundo Navarrete Md. Iqbal Hossain Stephen Kobourov 24 2 0 24 May 2022
Uniform Manifold Approximation with Two-phase Optimization Hyeon Jeon Hyung-Kwon Ko S. Lee Jaemin Jo Jinwook Seo 35 13 0 01 May 2022
Hierarchical Nearest Neighbor Graph Embedding for Efficient Dimensionality Reduction M. Sarfraz Marios Koulakis C. Seibold Rainer Stiefelhagen 28 19 0 24 Mar 2022
Incorporating Texture Information into Dimensionality Reduction for High-Dimensional Images Alexander Vieth Anna Vilanova B. Lelieveldt E. Eisemann T. Höllt 18 4 0 18 Feb 2022
On the Convergence of Clustered Federated Learning Ma Jie Guodong Long Dinesh Manocha Jing Jiang Chengqi Zhang FedML 39 46 0 13 Feb 2022
A Probabilistic Graph Coupling View of Dimension Reduction Hugues van Assel T. Espinasse J. Chiquet F. Picard 22 14 0 31 Jan 2022
DeepVisualInsight: Time-Travelling Visualization for Spatio-Temporal Causality of Deep Classification Training Xiangli Yang Yun Lin Ruofan Liu Zhenfeng He Chao Wang Jinlong Dong Hong Mei 14 5 0 31 Dec 2021
Network representation learning: A macro and micro view Xueyi Liu Jie Tang GNN AI4TS 19 23 0 21 Nov 2021
Scalable Graph Embedding LearningOn A Single GPU Azita Nouri Philip E. Davis P. Subedi M. Parashar GNN 36 1 0 13 Oct 2021
Cluster Analysis of a Symbolic Regression Search Space G. Kronberger Lukas Kammerer Bogdan Burlacu Stephan M. Winkler M. Kommenda M. Affenzeller 208 7 0 28 Sep 2021
Adaptive Neural Message Passing for Inductive Learning on Hypergraphs Devanshu Arya D. K. Gupta S. Rudinac M. Worring 52 12 0 22 Sep 2021
Uniform Manifold Approximation and Projection (UMAP) and its Variants: Tutorial and Survey Benyamin Ghojogh A. Ghodsi Fakhri Karray Mark Crowley 29 22 0 25 Aug 2021
Stochastic Cluster Embedding Zhirong Yang Yuwei Chen D. Sedov Samuel Kaski J. Corander 11 5 0 18 Aug 2021
Measuring and Explaining the Inter-Cluster Reliability of Multidimensional Projections Hyeon Jeon Hyung-Kwon Ko Jaemin Jo Youngtaek Kim Jinwook Seo 49 17 0 16 Jul 2021
An Analytical Survey on Recent Trends in High Dimensional Data Visualization Alex B. Kiefer Md. Khaledur Rahman AI4TS 14 2 0 05 Jul 2021
Statistical embedding: Beyond principal components D. Tjøstheim Martin Jullum Anders Løland 28 2 0 03 Jun 2021
On UMAP's true loss function Sebastian Damrich Fred Hamprecht 37 39 0 26 Mar 2021
Interpretable Machine Learning: Fundamental Principles and 10 Grand Challenges Cynthia Rudin Chaofan Chen Zhi Chen Haiyang Huang Lesia Semenova Chudi Zhong FaML AI4CE LRM 59 655 0 20 Mar 2021