rpotter6298
280060db82
- 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.
29 lines
1.1 KiB
JSON
29 lines
1.1 KiB
JSON
[
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{
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"_note": "Single-eye regression at nt=50, refugelike backbone. Eye-level fusion (no hb), regression heads predicting per-eye vf_md. Pairs with the bilateral baseline_reg_nt50 (mean-of-eyes target, hb fusion) for the worst-eye aggregation analysis: predict per-eye MD at nt, then aggregate to patient-level via min(OD_pred, OS_pred).",
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"run_name": "experiments/reg_head/single_eye_reg_nt50",
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"reps": 10,
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"overrides": {
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"label_filter": [0, 1, 2]
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},
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"stage_overrides": {
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"nt": { "epochs": 50 },
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"img_aux": {
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"module": "v4.classes.heads.regression",
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"class": "RegressionHead",
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"args": { "dropout": 0.3, "target_key": "vf_md", "loss": "mse" }
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},
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"cd_aux": {
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"module": "v4.classes.heads.regression",
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"class": "RegressionHead",
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"args": { "dropout": 0.3, "target_key": "vf_md", "loss": "mse" }
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},
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"nt_head": {
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"module": "v4.classes.heads.regression",
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"class": "RegressionHead",
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"args": { "dropout": 0.3, "target_key": "vf_md", "loss": "mse" }
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}
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}
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}
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]
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