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CellStrat > Research/Blog > Industry > Publishing
27
Aug
Working with Giant Graphs

#CellStratAILab #disrupt4.0 #WeCreateAISuperstars #WhereLearningNeverStops Recently, our AI Lab Researcher Gouthaman Asokan presented an excellent session on Giant Graphs, wherein we use specialized Graph Neural Networks to process and mine massive graphs – such as social networks or paper citation graphs. Examples of Real Life Giant Graphs Giant graphs has usually millions or billions of nodes […]

Posted in: Graph Neural Networks, Healthcare, Pharma, Publishing,
Tags: Bigraph, control variate sampling, giant graphs, graph neural networks, graph theory, GraphSage, knowledge graph, Knowledge Graphs, neighbor sampling, Node Flow, PubMed, Receptive Field, reddit dataset, SageNet, social network, social networks,
23
Jun
Relational GCN for Heterogeneous Graphs

#CellStratAILab #disrupt4.0 #WeCreateAISuperstars #WhereLearningNeverStops Recently, our AI Lab Researcher Gouthaman Asokan presented an amazing session on Relational Graphical Convolutional Networks (Relational GCN). These are particularly useful for mining heterogeneous groups. Table of Contents :- GCN HOMOGENEOUS AND HETEROGENEOUS GRAPHS KEY IDEAS OF RELATIONAL GCN FINDING PAGERANK USING MESSAGE PASSING BUILDING A RELATIONAL GCN FOR THE […]

Posted in: Graph Neural Networks, Publishing, Retail,
Tags: ACM Citation, Entity classification, GCN, GNN, graph analysis, Graph Convolutional Network, graph network, graph neural networks, graph theory, heterogenous graphs, homogeneous graphs, knowledge graph, Link Prediction, Message Passing, ontology, ontology graph, PageRank, pytorch, R-GCN, recommender systems, relational GCN,