Эксперимент: Directed distance-curvature positional encoding (#1291)

{ "worked": false, "confidence": 9, "verdict": "Built experiment.py with directed shortest-path curvature features, SVD pseudoinverse computation, a numerical system check, and a seeded low-label directed node-classification comparison. The systems were solved accurately with maximum residual 6.8e-12, and signed sums matched, but the claimed absolute l1 equality failed: all 20 graphs had signed curvature values, with mean absolute l1 mismatch 207.3 and maximum 2956.3. Curvature gave a small low-label accuracy increase from 0.465 to 0.479 and improved Brier score from 0.487 to 0.467, but at the higher label budget accuracy decreased from 0.521 to 0.511, so there is no consistent observed win and the stated l1 claim is contradicted for signed solutions.", "metrics": { "baseline": "5 labels/class: accuracy 0.4651 +/- 0.0353, Brier 0.4869; 10 labels/class: accuracy 0.5211 +/- 0.0271, Brier 0.4414", "idea": "5 labels/class: accuracy 0.4791 +/- 0.0604, Brier 0.4671; 10 labels/class: accuracy 0.5105 +/- 0.0466, Brier 0.4333; maximum linear-system residual 6.8e-12, mean absolute l1 mismatch 207.3" }, "how_to_run": "/home/maxwelhelp/main/bin/python3 experiment.py", "files": [ "experiment.py" ], "limitations": "Only a small synthetic 96-node graph task was tested; no citation or transaction graph, GAT or transformer attention variant, degree/PageRank/eigenvector controls, calibration curves, FLOP accounting, or extensive labeled-node budgets were evaluated. The experiment used five seeds and two label budgets." }