Эксперимент: Monotone Singular-Value ICNN Envelope (#1265)

{ "worked": true, "confidence": 8, "verdict": "Built a positive-singular-value ICNN with nonnegative softplus-parameterized weights, an SVD energy wrapper, lower-envelope penalty, and an unconstrained MLP baseline. The architectural claim was reproduced: the ICNN had 0% Jensen and monotonicity violations, versus 0.375% and 47.6% for the MLP; lower-bound violations fell from 47.7% to 36.1% on the unseen grid. This is a real structural signal, but not an overall accuracy or speed win: ICNN RMSE was 0.183 versus 0.083 and runtime was 9.27 versus 7.48 seconds.", "metrics": { "baseline": "MLP: 697 parameters, RMSE 0.0829, grid lower violation 47.67%, Jensen violation 0.375%, monotonicity violation 47.56%, training time 7.48 s", "idea": "Monotone ICNN: 543 parameters, RMSE 0.1829, grid lower violation 36.09%, Jensen violation 0%, monotonicity violation 0%, training time 9.27 s" }, "how_to_run": "/home/maxwelhelp/main/bin/python3 experiment.py", "files": [ "experiment.py", "results/metrics.json" ], "limitations": "This is a small 2D synthetic positive-singular-value experiment, not a Saint Venant–Kirchhoff or finite-element constitutive simulation. Stress accuracy, optimization stability through SVD gradients, FLOP-normalized comparisons, larger dimensions, repeated random seeds, and a true numerically computed polyconvex envelope were not tested." }