23 citations · 29 across the 10 of their papers we have counts for
12 papers
A Scalable Method for Readable Tree Layouts
Kathryn Gray, Mingwei Li, Reyan Ahmed +4
Large tree structures are ubiquitous and real-world relational datasets often have information associated with nodes (e.g., labels or other attributes) and edges (e.g., weights or…
Triple Sparsification of Graph Convolutional Networks without Sacrificing the Accuracy
Md. Khaledur Rahman, Ariful Azad
Graph Neural Networks (GNNs) are widely used to perform different machine learning tasks on graphs. As the size of the graphs grows, and the GNNs get deeper, training and inference…
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…
A Comprehensive Analytical Survey on Unsupervised and Semi-Supervised Graph Representation Learning Methods
Md. Khaledur Rahman, Ariful Azad
Graph representation learning is a fast-growing field where one of the main objectives is to generate meaningful representations of graphs in lower-dimensional spaces. The learned…
Complexity for Open Quantum System
Arpan Bhattacharyya, Tanvir Hanif, S. Shajidul Haque +1
We study the complexity for an open quantum system. Our system is a harmonic oscillator coupled to a one-dimensional massless scalar field, which acts as the bath. Specifically, we…
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…
Prefix Block-Interchanges on Binary and Ternary Strings
Md. Khaledur Rahman, M. Sohel Rahman
The genome rearrangement problem computes the minimum number of operations that are required to sort all elements of a permutation. A block-interchange operation exchanges two bloc…
NEDindex: A new metric for community structure in networks
Md. Khaledur Rahman
There are several metrics (Modularity, Mutual Information, Conductance, etc.) to evaluate the strength of graph clustering in large graphs. These metrics have great significance to…