
In this blog, we will summarize the latex code of equations of Graph Neural Network(GNN) models, which are useful as quick reference for your research. For common notation, we denote G=(V,E) as the graph. V as the set of nodes with size V=N, and E as the set of N_e edges as E = N_e. A is denoted as the adjacency matrix. For each node v, we use h_v and o_v as hidde state and output vector of each node.
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This blog summarizes the latest research development of GNN papers published in KDD2023 conferences. This year there are total 9 papers related to GNN in KDD2023. Most of the authors' affiliations are top research institutes (Google Research, DeepMind, Meta FAIR) and universities (Stanford, Berkeley, MIT, CMU and others).

This blog summarizes the latest research development of Knowledge Graph papers published in KDD2023 conferences. This year there are total 11 papers related to Knowledge Graph in KDD2023. Most of the authors' affiliations are top research institutes (Google Research, DeepMind, Meta FAIR) and universities (Stanford, Berkeley, MIT, CMU and others).