2 citations · 3 across the 4 of their papers we have counts for
5 papers
Barlow Graph Auto-Encoder for Unsupervised Network Embedding
Rayyan Ahmad Khan, Martin Kleinsteuber
Network embedding has emerged as a promising research field for network analysis. Recently, an approach, named Barlow Twins, has been proposed for self-supervised learning in compu…
A Framework for Joint Unsupervised Learning of Cluster-Aware Embedding for Heterogeneous Networks
Rayyan Ahmad Khan, Martin Kleinsteuber
Heterogeneous Information Network (HIN) embedding refers to the low-dimensional projections of the HIN nodes that preserve the HIN structure and semantics. HIN embedding has emerge…
Variational Embeddings for Community Detection and Node Representation
Rayyan Ahmad Khan, Muhammad Umer Anwaar, Omran Kaddah +1
In this paper, we study how to simultaneously learn two highly correlated tasks of graph analysis, i.e., community detection and node representation learning. We propose an efficie…
Epitomic Variational Graph Autoencoder
Rayyan Ahmad Khan, Muhammad Umer Anwaar, Martin Kleinsteuber
Variational autoencoder (VAE) is a widely used generative model for learning latent representations. Burda et al. in their seminal paper showed that learning capacity of VAE is lim…
Extended Affinity Propagation: Global Discovery and Local Insights
Rayyan Ahmad Khan, Rana Ali Amjad, Martin Kleinsteuber
We propose a new clustering algorithm, Extended Affinity Propagation, based on pairwise similarities. Extended Affinity Propagation is developed by modifying Affinity Propagation s…