Re:Graph theory, graph convolutional networks, knowledge graphs
by hansvm on Sunday February 07, 2021 @11:18PM
(#26060730)
> Graph embedding algorithms for euclidean space are flawed because you essentially need to add an additional dimension for every node.
A euclidean embedding can't even approximately embed a graph as simple as C4, no matter how many dimensions you add. Nevertheless, I've been surprised at how good the results have been when blindly embedding stuff in euclidean space (e.g., word2vec) given the high error floor for any possible such embedding.
A euclidean embedding can't even approximately embed a graph as simple as C4, no matter how many dimensions you add. Nevertheless, I've been surprised at how good the results have been when blindly embedding stuff in euclidean space (e.g., word2vec) given the high error floor for any possible such embedding.