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Graph Networks: composable edge, node and global update blocks

Defined a composable graph-network block with edge/node/global attributes, learned updates and permutation-invariant aggregations, unifying structured neural reasoning interfaces.

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Defined a composable graph-network block with edge/node/global attributes, learned updates and permutation-invariant aggregations, unifying structured neural reasoning interfaces.

Source-linked catalogue note. A detailed explanatory guide has not yet been prepared for this entry.

Scientific scope

Part review/position paper, part formal interface synthesis; predecessors retain their inventions. Relational inductive bias supports structured modeling but does not prove universal compositional generalization, exact physical laws or human-level reasoning. Original27named front controls, not later GraphNets library maintainers.

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People and systems

Peter W. Battaglia; Jessica B. Hamrick; Victor Bapst; Alvaro Sanchez-Gonzalez; Vinicius Zambaldi; Mateusz Malinowski; Andrea Tacchetti; David Raposo; Adam Santoro; Ryan Faulkner; Caglar Gulcehre; Francis Song; Andrew Ballard; Justin Gilmer; George Dahl; Ashish Vaswani; Kelsey Allen; Charles Nash; Victoria Langston; Chris Dyer; Nicolas Heess; Daan Wierstra; Pushmeet Kohli; Matt Botvinick; Oriol Vinyals; Yujia Li; Razvan Pascanu

Source-listed authors or explicitly credited technical contributors for the cited versions. Family entries retain source-specific attribution; a combined list is not one original-paper byline or equal individual work. Names alone do not establish resolved identities.

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English catalogue narrative

Graph Networks: composable edge, node and global update blocks

Defined a composable graph-network block with edge/node/global attributes, learned updates and permutation-invariant aggregations, unifying structured neural reasoning interfaces.

Scientific scope

Part review/position paper, part formal interface synthesis; predecessors retain their inventions. Relational inductive bias supports structured modeling but does not prove universal compositional generalization, exact physical laws or human-level reasoning. Original27named front controls, not later GraphNets library maintainers.

Reading status

This is a source-linked WRS catalogue note. A full explanatory guide and independent scientific reconstruction have not been completed for this entry. Read the identified original work for its complete narrative and arguments.

People and systems

Peter W. Battaglia; Jessica B. Hamrick; Victor Bapst; Alvaro Sanchez-Gonzalez; Vinicius Zambaldi; Mateusz Malinowski; Andrea Tacchetti; David Raposo; Adam Santoro; Ryan Faulkner; Caglar Gulcehre; Francis Song; Andrew Ballard; Justin Gilmer; George Dahl; Ashish Vaswani; Kelsey Allen; Charles Nash; Victoria Langston; Chris Dyer; Nicolas Heess; Daan Wierstra; Pushmeet Kohli; Matt Botvinick; Oriol Vinyals; Yujia Li; Razvan Pascanu

Source-listed authors or explicitly credited technical contributors for the cited versions. Family entries retain source-specific attribution; a combined list is not one original-paper byline or equal individual work. Names alone do not establish resolved identities.

Original sources