What is recorded here?
Predicts particle mobility and rearrangement in simulated glassy systems from graph-encoded initial structure, and probes spatial correlations learned by the network.
Source-linked catalogue note. A detailed explanatory guide has not yet been prepared for this entry.
Scientific scope
The source-supported claim concerns learned structural representations and prediction of particle dynamics. A learned correlation length is not directly a measured physical quantity or a solution of glass-transition theory. The later code/data-link correction is not a new discovery.
Read the original work
- Unveiling the predictive power of static structure in glassy systems
- Towards understanding glasses with graph neural networks
- Author Correction: Unveiling the predictive power of static structure in glassy systems
This English explanation is an editorial reading view. It does not replace the complete original work or certify its science.
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People and systems
V. Bapst; T. Keck; A. Grabska-Barwińska; C. Donner; E. D. Cubuk; S. S. Schoenholz; A. Obika; A. W. R. Nelson; T. Back; D. Hassabis; P. Kohli
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-network prediction of glassy dynamics from static structure
Predicts particle mobility and rearrangement in simulated glassy systems from graph-encoded initial structure, and probes spatial correlations learned by the network.
Scientific scope
The source-supported claim concerns learned structural representations and prediction of particle dynamics. A learned correlation length is not directly a measured physical quantity or a solution of glass-transition theory. The later code/data-link correction is not a new discovery.
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
V. Bapst; T. Keck; A. Grabska-Barwińska; C. Donner; E. D. Cubuk; S. S. Schoenholz; A. Obika; A. W. R. Nelson; T. Back; D. Hassabis; P. Kohli
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.