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05/17/2023
A Scalable Method for Readable Tree Layouts
Large tree structures are ubiquitous and real-world relational datasets ...
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08/06/2022
Triple Sparsification of Graph Convolutional Networks without Sacrificing the Accuracy
Graph Neural Networks (GNNs) are widely used to perform different machin...
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02/05/2022
MarkovGNN: Graph Neural Networks on Markov Diffusion
Most real-world networks contain well-defined community structures where...
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12/20/2021
A Comprehensive Analytical Survey on Unsupervised and Semi-Supervised Graph Representation Learning Methods
Graph representation learning is a fast-growing field where one of the m...
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07/05/2021
An Analytical Survey on Recent Trends in High Dimensional Data Visualization
Data visualization is the process by which data of any size or dimension...
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11/07/2020
FusedMM: A Unified SDDMM-SpMM Kernel for Graph Embedding and Graph Neural Networks
We develop a fused matrix multiplication kernel that unifies sampled den...
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09/17/2020
Force2Vec: Parallel force-directed graph embedding
A graph embedding algorithm embeds a graph into a low-dimensional space ...
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08/19/2020
Training Sensitivity in Graph Isomorphism Network
Graph neural network (GNN) is a popular tool to learn the lower-dimensio...
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02/11/2020
BatchLayout: A Batch-Parallel Force-Directed Graph Layout Algorithm in Shared Memory
Force-directed algorithms are widely used to generate aesthetically plea...
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05/20/2019