Mesh-based Super-resolution of Multiscale Detonation Flows with Graph Transformers

arXiv:2511.12041 · cs.LG, cs.AI · Submitted 2025-11-15 · Read on arXiv

cs.LG, cs.AI

Submitted: 2025-11-15

Updated: 2026-09-13

License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Terminology

• Transformer — 20× in this paper · explained in 2 episodes
• Accuracy — 3× in this paper · explained in 1 episode
• Clustering — 3× in this paper · explained in 2 episodes
• Fidelity — 3× in this paper · explained in 2 episodes
• Diffusion Model — 2× in this paper · explained in 8 episodes
• Embeddings — 2× in this paper · explained in 2 episodes
• Adam — 1× in this paper · explained in 2 episodes
• AdamW Optimizer — 1× in this paper · explained in 1 episode
• DeepONet — 1× in this paper · explained in 2 episodes
• GNNs — 1× in this paper · explained in 2 episodes
• Loss Function — 1× in this paper · explained in 2 episodes
• Mode Collapse — 1× in this paper · explained in 2 episodes
• Point Clouds — 1× in this paper · explained in 2 episodes
• Representation Learning — 1× in this paper · explained in 2 episodes
• Tokenization — 1× in this paper · explained in 2 episodes
• Transfer Learning — 1× in this paper · explained in 10 episodes

Sources

• Fast Graph Representation Learning with PyTorch Geometric

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