Table 1:

Network performance across architectures and regularization strength λ. MLP / U-Net perform best. All methods work.

MNIST
Network →	MLP		Enc-Dec		U-Net		ConvOnly
λ ↓	Dice	Folds	Dice	Folds	Dice	Folds	Dice	Folds
64	0.92	26.61	0.80	0.15	0.93	3.87	0.93	30.20
128	0.92	9.95	0.77	0.08	0.92	1.45	0.90	16.27
256	0.91	2.48	0.72	0.01	0.90	0.41	0.88	7.17
512	0.90	0.72	0.66	0.03	0.89	0.09	0.85	3.12
1,024	0.88	0.34	0.62	0.06	0.86	0.02	0.81	0.54
2,048	0.87	0.16	0.63	0.00	0.73	0.09	0.76	0.07
Triangles & Circles
Network →	MLP		Enc-Dec		U-Net		ConvOnly
λ ↓	Dice	Folds	Dice	Folds	Dice	Folds	Dice	Folds
64	0.98	1.24	0.94	3.50	0.98	2.74	0.97	12.57
128	0.98	0.73	0.90	2.71	0.98	1.59	0.96	10.15
256	0.98	0.27	0.88	1.11	0.97	1.14	0.96	8.49
512	0.97	0.10	0.87	0.65	0.96	0.70	0.94	6.61
1,024	0.96	0.03	0.86	0.22	0.95	0.25	0.92	3.91
2,048	0.95	0.03	0.85	0.15	0.94	0.09	0.89	2.18