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@@ -133,6 +133,9 @@ structbench-train --mode train --config configs/wave_propagation_1d/cgn.toml \
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  ## References
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  - **CGN** — Li, Q., Wang, Z., Li, L., Hao, H., Chen, W., & Shao, Y. (2023). Machine learning prediction of structural dynamic responses using graph neural networks. *Computers & Structures*, 289, 107188. https://doi.org/10.1016/j.compstruc.2023.107188
 
 
 
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  ## Citation
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  ## References
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  - **CGN** — Li, Q., Wang, Z., Li, L., Hao, H., Chen, W., & Shao, Y. (2023). Machine learning prediction of structural dynamic responses using graph neural networks. *Computers & Structures*, 289, 107188. https://doi.org/10.1016/j.compstruc.2023.107188
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+ - **MGN** — Pfaff, T., Fortunato, M., Sanchez-Gonzalez, A., & Battaglia, P. W. (2021). Learning Mesh-Based Simulation with Graph Networks. *ICLR*. https://arxiv.org/abs/2010.03409
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+ - **Transolver** — Wu, H., Luo, H., Wang, H., Wang, J., & Long, M. (2024). Transolver: A Fast Transformer Solver for PDEs on General Geometries. *ICML*. https://arxiv.org/abs/2402.02366
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+ - **GeoFLARE** — Adams, R., et al. (NVIDIA). GeoTransolver. arXiv:2512.20399; with Puri, R., et al. FLARE: Fast Low-rank Attention Routing Engine. arXiv:2508.12594. GeoFLARE is GeoTransolver with the FLARE attention backend (attention_type GALE_FA; ADR-0045).
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  ## Citation
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