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Vikram Deshpande

1 accepted papers

2024

Energy-conserving equivariant GNN for elasticity of lattice architected metamaterials

ICLR 2024poster

Lattices are architected metamaterials whose properties strongly depend on their geometrical design. The analogy between lattices and graphs enables the use of graph neural networks (GNNs) as a faster surrogate model compared to traditional methods such as finite element modelling. In this work, we…