ScaGNN: a Graph Neural Network for Multiple Scattering Simulations
cs.LG
Submitted: 2026-09-29
Updated: 2026-09-29
Code: https://github.com/LARIAD/ScaGNN
Sources
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- Linear Attention with Global Context: A Multipole Attention Mechanism for Vision and Physics
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- GPU accelerated fast multipole boundary element method for simulation of 3D bubble dynamics in potential flow
- Categorical Reparameterization with Gumbel-Softmax
- The Concrete Distribution: A Continuous Relaxation of Discrete Random Variables
- Solving Partial Differential Equations in Different Domains by Operator Learning method Based on Boundary Integral Equations
- Probabilistically Rewired Message-Passing Neural Networks
- Learnt Sparsification for Interpretable Graph Neural Networks
- DropEdge: Towards Deep Graph Convolutional Networks on Node Classification
- Understanding over-squashing and bottlenecks on graphs via curvature
- Geometry Aware Operator Transformer as an Efficient and Accurate Neural Surrogate for PDEs on Arbitrary Domains
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