2 citations · 2 across the 4 of their papers we have counts for
7 papers
MarkovGNN: Graph Neural Networks on Markov Diffusion
Md. Khaledur Rahman, Abhigya Agrawal, Ariful Azad
Most real-world networks contain well-defined community structures where nodes are densely connected internally within communities. To learn from these networks, we develop MarkovG…
An Analytical Survey on Recent Trends in High Dimensional Data Visualization
Alexander Kiefer, Md. Khaledur Rahman
Data visualization is the process by which data of any size or dimensionality is processed to produce an understandable set of data in a lower dimensionality, allowing it to be man…
FusedMM: A Unified SDDMM-SpMM Kernel for Graph Embedding and Graph Neural Networks
Md. Khaledur Rahman, Majedul Haque Sujon, Ariful Azad
We develop a fused matrix multiplication kernel that unifies sampled dense-dense matrix multiplication and sparse-dense matrix multiplication under a single operation called FusedM…
Force2Vec: Parallel force-directed graph embedding
Md. Khaledur Rahman, Majedul Haque Sujon, Ariful Azad
A graph embedding algorithm embeds a graph into a low-dimensional space such that the embedding preserves the inherent properties of the graph. While graph embedding is fundamental…
Training Sensitivity in Graph Isomorphism Network
Md. Khaledur Rahman
Graph neural network (GNN) is a popular tool to learn the lower-dimensional representation of a graph. It facilitates the applicability of machine learning tasks on graphs by incor…
BatchLayout: A Batch-Parallel Force-Directed Graph Layout Algorithm in Shared Memory
Md. Khaledur Rahman, Majedul Haque Sujon, Ariful Azad
Force-directed algorithms are widely used to generate aesthetically pleasing layouts of graphs or networks arisen in many scientific disciplines. To visualize large-scale graphs, s…