In this blog, we will summarize the latex code of most fundamental and popular knowledge graph (KG) Equations, with special focus on the link prediction tasks. We will cover a wide range of models, including TransE, TransR, TransE, RotatE, SME(Linear), SimplE etc. Knowledge Graph consists of a set of triples [(h, r, t)]. h and t denotes the head node and tail node respectively. And r denotes multiple relation types. One common solution to the link prediction tasks is to learn low-dimensional embeddings of entities(E) and relations (R), and infer the missing part of [(?, r, t), (h, ?, t), (h, r, ?)].

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).