Table 2. Number of degenerate cases per parameter on 10,000 noisy simulations (Rician noise with SNR = 50).

Training and estimations of the posterior distributions were performed using a GPU. Time for training each model and time for estimating posterior distributions of 10,000 noisy simulations, define if they are degenerate or not, and extract the Maximum A Posteriori (MAP), uncertainty, and ambiguity are also reported.

Model (SNR = 50)	Training time (CPU)	Fitting time (on 10,000 simulations)	Number of degeneracies (on 10,000 simulations)
			${\displaystyle f_n}$	${\displaystyle D_n}$	${\displaystyle D_e^{\parallel }}$	${\displaystyle ODI}$	${\displaystyle D_e^{\mathrm{\perp }}}$	${\displaystyle f_s}$	${\displaystyle f_e}$	${\displaystyle C_s}$
Model 1: Ball&Stick	26 min	79 s	0	0	0	-	-	-	-	-
Model 2: Standard Model	42 min	82 s	75	71	117	109	29	-	-	-
Model 3: Extended-SANDI model	50 min	238 s	47	24	784	6	-	828	1047	56