145 citations · 303 across the 28 of their papers we have counts for
30 papers
On Leveraging Variational Graph Embeddings for Open World Compositional Zero-Shot Learning
Muhammad Umer Anwaar, Zhihui Pan, Martin Kleinsteuber
Humans are able to identify and categorize novel compositions of known concepts. The task in Compositional Zero-Shot learning (CZSL) is to learn composition of primitive concepts,…
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…
Metapath- and Entity-aware Graph Neural Network for Recommendation
Muhammad Umer Anwaar, Zhiwei Han, Shyam Arumugaswamy +6
In graph neural networks (GNNs), message passing iteratively aggregates nodes' information from their direct neighbors while neglecting the sequential nature of multi-hop node conn…
Compositional Learning of Image-Text Query for Image Retrieval
Muhammad Umer Anwaar, Egor Labintcev, Martin Kleinsteuber
In this paper, we investigate the problem of retrieving images from a database based on a multi-modal (image-text) query. Specifically, the query text prompts some modification in…