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hypertower/v4/configs/clinical_solo_bilateral.json
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rpotter6298 280060db82 Add new regression and ensemble experiment configurations for V2-M and OrthoBridge
- Introduced multiple regression experiment configurations targeting vf_md, including:
  - cd_solo_reg_set.json: CD tower only regression setup.
  - img_solo_reg_set.json: Image tower only regression setup.
  - reg_head_epoch_sweep.json: Baseline regression sweeps at different epochs (50, 75, 100).
  - reg_head_set.json: Various regression setups including baseline and OrthoBridge configurations.
  - single_eye_reg.json: Single-eye regression setup for worst-eye aggregation analysis.

- Added ensemble configurations for OrthoBridge with different inner bridges:
  - ortho_alts_ensemble.json: Ensemble tests with ConcatBridge, PairwiseAdditiveBridge, and GatedAdditiveBridge.
  - ortho_alts_tritower.json: Tritower tests with the same inner bridges.

- Created V2-M specific configurations:
  - baseline_reg_nt50.json: Regression baseline with V2-M backbone.
  - geom_vec_gt.json and geom_vec_unet.json: Geometry vector injection experiments with V2-M.
  - single_l1_bridges.json: Single-eye ensemble experiments with various bridge types.
  - tritower_geom_gt.json: Tritower setup with GT contour-rasterized masks.

- Promoted existing experiments to higher repetitions for robustness.
2026-06-11 15:08:20 +02:00

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{
"_notes": [
"Clinical-only at patient level (bilateral). Mirrors clinical_solo.json but",
"adds the hb stage so cd_fuse(OD) and cd_fuse(OS) are aggregated at",
"patient level. Pairs with single-eye clinical_solo for the Figure 4",
"bilateral comparison."
],
"run_name": "v4/clinical_solo_bilateral",
"num_classes": 2,
"label_filter": [0, 1],
"split_identity_level": 1,
"eval_stage": "hb",
"save_predictions": true,
"seed": 1234,
"folds": 5,
"fold_seed": 100,
"output_root": "v4/results",
"out_dir_tags": ["binary"],
"data": {
"module": "v4.classes.profiles.v4papila",
"args": {
"image_dir": "Papila/FundusImages",
"clinical_dir": "Papila/ClinicalData",
"label_col": "Diagnosis",
"iop_corr_method": "ratio",
"iop_drop_raw": true,
"exclude_cols": ["Axial_Length"],
"in_memory_cache": false
}
},
"towers": [
{
"name": "cd",
"module": "v4.classes.towers.clinical_tower",
"class": "ClinicalEncoder",
"data_source": "matrix",
"args": { "hidden_dim": 128 }
}
],
"stages": [
{
"name": "cd_warm",
"type": "warm",
"tower": "cd",
"head_name": "cd_aux",
"level": "eye",
"epochs": 40
},
{
"name": "cd_aux",
"type": "head",
"input": "cd",
"train_with": "cd_fuse"
},
{
"name": "cd_fuse",
"type": "fusion",
"module": "v4.classes.bridges.mono_bridge",
"class": "MonoBridge",
"inputs": ["cd"],
"level": "eye",
"epochs": 36,
"train_towers": true,
"args": { "use_ln": false }
},
{
"name": "hb",
"type": "fusion",
"module": "v4.classes.bridges.hyperbridge",
"class": "HyperBridge",
"inputs": { "a": "cd_fuse", "b": "cd_fuse" },
"level": "patient",
"epochs": 10,
"args": { "hidden_dim": 256, "mode": "embedding_mlp" }
},
{
"name": "hb_head",
"type": "head",
"input": "hb",
"train_with": "hb",
"args": { "dropout": 0.3 }
}
],
"training": {
"lr": 1e-4,
"batch_size": 16,
"tune_binary_threshold": true
}
}