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Multiplex Molecular Graph Neural Network

MXMNet

1 paper tagged archive 2025-07-28

Introduced by Shuo Zhang et al. in Molecular Mechanics-Driven Graph Neural Network with Multiplex Graph for Molecular Structures

archive 2025-07-28 Description, source and code snippet are the archive's method entry.

The Multiplex Molecular Graph Neural Network (MXMNet) is an approach for the representation learning of molecules. The molecular interactions are divided into two categories: local and global. Then a two-layer multiplex graph G = Gₗ, G_g is constructed for a molecule. In G, the local layer Gₗ only contains the local connections that mainly capture covalent interactions, and the global layer G_g contains the global connections that cover non-covalent interactions. MXMNet uses the Multiplex Molecular (MXM) module that contains a novel angle-aware message passing operated on Gₗ and an efficient message passing operated on G_g.

PaperSource

Papers archive 2025-07-28

1 shown of 1, newest first. Repository counts are the archive's code-links table. A Syntology line states what Syntology ran from that paper's harvested code; it is per sample and not a correctness claim.

Tasks archive 2025-07-28

3 tasks the archive attaches to papers tagged with this method, by distinct papers. A task without a page in the catalog is plain text.

TaskPapers
Drug Discovery1
Formation Energy1
Graph Neural Network1

Usage over time archive 2025-07-28

Papers per year tagged with MXMNet: 2020 to 2020, peak 1 1 0 2020: 1 paper 2020
Papers per year the archive tags with this method, by the paper's archive date (1 dated). Bars are counts, not a trend claim.

Components: the archive holds no method-to-method composition, so PwC's Components table cannot be rebuilt; the Papers list carries no Results column for the same reason (the archive does not join its leaderboard rows to method tags).

Categories archive 2025-07-28

Graph Models

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