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07/05/2023
TransformerG2G: Adaptive time-stepping for learning temporal graph embeddings using transformers
Dynamic graph embedding has emerged as a very effective technique for ad...
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05/16/2022
Scalable algorithms for physics-informed neural and graph networks
Physics-informed machine learning (PIML) has emerged as a promising new ...
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09/28/2021
DynG2G: An Efficient Stochastic Graph Embedding Method for Temporal Graphs
Dynamic graph embedding has gained great attention recently due to its c...
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06/05/2021
AOSLO-net: A deep learning-based method for automatic segmentation of retinal microaneurysms from adaptive optics scanning laser ophthalmoscope images
Adaptive optics scanning laser ophthalmoscopy (AOSLO) provides real-time...
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12/15/2020
Understanding graph embedding methods and their applications
Graph analytics can lead to better quantitative understanding and contro...
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05/08/2020
A Graph Gaussian Embedding Method for Predicting Alzheimer's Disease Progression with MEG Brain Networks
Characterizing the subtle changes of functional brain networks associate...
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10/07/2019
Multi-label Detection and Classification of Red Blood Cells in Microscopic Images
Cell detection and cell type classification from biomedical images play ...
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10/23/2017