{
  "paper": "Topology-Agnostic Graph U-Nets for Scalar Field Prediction on Unstructured Meshes (Ferguson et al., 2024)",
  "adaptation": "3-level kd-tree TAG U-Net denoiser; source paper is direct scalar regression, not DDPM",
  "pooling": "balanced kd-tree leaves, at most 8 3-D nodes; mean pool / copied unpool",
  "convolution": "EdgeConv max aggregation with CAD coordinates each convolution",
  "level_0": "prepared CAD edge_index with explicit relative delta xyz and Euclidean edge length",
  "coarse_levels": "12-NN bidirectional edges after each pool, with relative delta xyz and Euclidean length recomputed from coarse coordinates",
  "sizes": [
    6155,
    1024,
    128,
    16
  ],
  "edges": [
    36480,
    14404,
    1782,
    222
  ],
  "condition": "same XLS/global heater values and validity mask as graph_6000",
  "production_valid": false,
  "limitations": [
    "1 NG run(s), no held-out test",
    "registration and defect extents unvalidated",
    "heater footprints unavailable; local heater projection mask false"
  ]
}