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07/14/2023
DistTGL: Distributed Memory-Based Temporal Graph Neural Network Training
Memory-based Temporal Graph Neural Networks are powerful tools in dynami...
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06/05/2023
Graph-Aware Language Model Pre-Training on a Large Graph Corpus Can Help Multiple Graph Applications
Model pre-training on large text corpora has been demonstrated effective...
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06/01/2023
SpotTarget: Rethinking the Effect of Target Edges for Link Prediction in Graph Neural Networks
Graph Neural Networks (GNNs) have demonstrated promising outcomes across...
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02/27/2023
IGB: Addressing The Gaps In Labeling, Features, Heterogeneity, and Size of Public Graph Datasets for Deep Learning Research
Graph neural networks (GNNs) have shown high potential for a variety of ...
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02/24/2023
PaGE-Link: Path-based Graph Neural Network Explanation for Heterogeneous Link Prediction
Transparency and accountability have become major concerns for black-box...
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01/18/2023
ReFresh: Reducing Memory Access from Exploiting Stable Historical Embeddings for Graph Neural Network Training
A key performance bottleneck when training graph neural network (GNN) mo...
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01/16/2023
PIGEON: Optimizing CUDA Code Generator for End-to-End Training and Inference of Relational Graph Neural Networks
Relational graph neural networks (RGNNs) are graph neural networks (GNNs...
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06/22/2022
Efficient and effective training of language and graph neural network models
Can we combine heterogenous graph structure with text to learn high-qual...
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05/24/2022
ColdGuess: A General and Effective Relational Graph Convolutional Network to Tackle Cold Start Cases
Low-quality listings and bad actor behavior in online retail websites th...
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03/28/2022
TGL: A General Framework for Temporal GNN Training on Billion-Scale Graphs
Many real world graphs contain time domain information. Temporal Graph N...
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12/31/2021
Distributed Hybrid CPU and GPU training for Graph Neural Networks on Billion-Scale Graphs
Graph neural networks (GNN) have shown great success in learning from gr...
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11/23/2021
Network In Graph Neural Network
Graph Neural Networks (GNNs) have shown success in learning from graph s...
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11/10/2021
Graph Neural Network Training with Data Tiering
Graph Neural Networks (GNNs) have shown success in learning from graph-s...
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10/11/2020
DistDGL: Distributed Graph Neural Network Training for Billion-Scale Graphs
Graph neural networks (GNN) have shown great success in learning from gr...
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07/24/2020
COVID-19 Knowledge Graph: Accelerating Information Retrieval and Discovery for Scientific Literature
The coronavirus disease (COVID-19) has claimed the lives of over 350,000...
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05/21/2020
Repurpose Open Data to Discover Therapeutics for COVID-19 using Deep Learning
There have been more than 850,000 confirmed cases and over 48,000 deaths...
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04/18/2020