May 31, 2024 · In this paper, we propose a novel approach to alleviate this problem by approximating the input graph as an intersecting community graph (ICG) ...
May 31, 2024 · In this paper, we propose a novel approach to alleviate this problem by approximating the input graph as an intersecting community graph (ICG) – ...
In this paper, we propose a novel approach to alleviate this problem by approximating the input graph as an intersecting community graph (ICG) -- a combination ...
This offers a new and fundamentally different pipeline for learning on very large non-sparse graphs, whose applicability is demonstrated empirically on node ...
Learning on Large Graphs using Intersecting Communities. Ben Finkelshtein‚ İsmail İlkan Ceylan‚ Michael Bronstein and Ron Levie. Book Title.
Jun 5, 2024 · In this paper, we propose a novel approach to alleviate this problem by approximating the input graph as an intersecting community graph (ICG) ...
Jun 2, 2024 · This paper introduces a novel approach for learning on large graphs by leveraging the hierarchical community structure often found in real-world ...
Jun 24, 2024 · Bibliographic details on Learning on Large Graphs using Intersecting Communities.
Jun 7, 2014 · I have a very large directed graph (a social network graph) with about 8 million nodes. I would like to run a community detection algorithm on ...
Missing: Intersecting | Show results with:Intersecting
Sep 26, 2024 · MPNNs iteratively update each node's representation in an input graph by aggregating messages from the node's...