TRACE: A spatiotemporal contact memory graph network simulator for granular dynamics
cs.LG, cs.NA, math.NA, stat.ML
Submitted: 2026-09-02
Updated: 2026-09-26
Code: https://github.com/Data-Driven-Computational-Geotechnics/TRACE
License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Terminology
Sources
- Relational inductive biases, deep learning, and graph networks
- Learning Mesh-Based Simulation with Graph Networks
- Learning Particle Dynamics for Manipulating Rigid Bodies, Deformable Objects, and Fluids
- Geometric and Physical Quantities Improve E(3) Equivariant Message Passing
- Equivariant Graph Mechanics Networks with Constraints
- Lagrangian Neural Networks
- Differentiable Graph Neural Network Simulator for the Back-Analysis of Post-Liquefaction Residual Strength from Flow Failure Runout
- Learning 3D Granular Flow Simulations
- Parameter-Efficient Conditioning for Material Generalization in Graph-Based Simulators
- WorldParticle: Unified World Simulation of Lagrangian Particle Dynamics via Transformer
- Temporal Graph Networks for Deep Learning on Dynamic Graphs
- Inductive Representation Learning on Temporal Graphs
- Graph Attention Networks
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