Network Embedding Exploration Tool (NEExT)

20 March 2025

Papers citing "Network Embedding Exploration Tool (NEExT)"

9 / 9 papers shown

Title
Properties and Performance of the ABCDe Random Graph Model with Community Structure Bogumil Kamiñski Tomasz Olczak Bartosz Pankratz P. Prałat Franccois Théberge 27 12 0 28 Mar 2022
Modularity of the ABCD Random Graph Model with Community Structure B. Kamiński Bartosz Pankratz P. Prałat F. Théberge 31 16 0 03 Mar 2022
A Multi-purposed Unsupervised Framework for Comparing Embeddings of Undirected and Directed Graphs Bogumil Kamiñski Ł. Kraiński P. Prałat F. Théberge 52 8 0 30 Nov 2021
Learning in High Dimension Always Amounts to Extrapolation Randall Balestriero J. Pesenti Yann LeCun 129 104 0 18 Oct 2021
Wasserstein Weisfeiler-Lehman Graph Kernels Matteo Togninalli M. Ghisu Felipe Llinares-López Bastian Rieck Karsten Borgwardt 76 201 0 04 Jun 2019
UMAP: Uniform Manifold Approximation and Projection for Dimension Reduction Leland McInnes John Healy James Melville 202 9,479 0 09 Feb 2018
graph2vec: Learning Distributed Representations of Graphs A. Narayanan Mahinthan Chandramohan R. Venkatesan Lihui Chen Yang Liu Shantanu Jaiswal GNN 79 745 0 17 Jul 2017
subgraph2vec: Learning Distributed Representations of Rooted Sub-graphs from Large Graphs A. Narayanan Mahinthan Chandramohan Lihui Chen Yang Liu S. Saminathan GNN 66 157 0 29 Jun 2016
Sinkhorn Distances: Lightspeed Computation of Optimal Transportation Distances Marco Cuturi OT 220 4,289 0 04 Jun 2013