What is recorded here?
Learns particle dynamics by graph encode–process–decode message passing, then extends this learned-simulation approach to irregular meshes using mesh-space/world-space edges and a predicted sizing field with a generic remesher.
Source-linked catalogue note. A detailed explanatory guide has not yet been prepared for this entry.
Scientific scope
One simulator-family record with source-specific bylines. GNS first four and MeshGraphNets first three authors explicitly share contribution. Rollout transfer and speed are empirical, not exact conservation, controlled global-error guarantees or universal replacement of numerical solvers. Model inference cost excludes training and producing reference simulations.
Read the original work
- Learning to Simulate Complex Physics with Graph Networks
- Learning Mesh-Based Simulation with Graph Networks
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
Alvaro Sanchez-Gonzalez; Jonathan Godwin; Tobias Pfaff; Rex Ying; Jure Leskovec; Peter W. Battaglia; Meire Fortunato
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.
Research locations and affiliations
Location not yet established
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English catalogue narrative
Graph Network Simulators and MeshGraphNets
Learns particle dynamics by graph encode–process–decode message passing, then extends this learned-simulation approach to irregular meshes using mesh-space/world-space edges and a predicted sizing field with a generic remesher.
Scientific scope
One simulator-family record with source-specific bylines. GNS first four and MeshGraphNets first three authors explicitly share contribution. Rollout transfer and speed are empirical, not exact conservation, controlled global-error guarantees or universal replacement of numerical solvers. Model inference cost excludes training and producing reference simulations.
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
Alvaro Sanchez-Gonzalez; Jonathan Godwin; Tobias Pfaff; Rex Ying; Jure Leskovec; Peter W. Battaglia; Meire Fortunato
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.