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System Identification on Robot Arm

16.57RMSE

Deep Ensemble

Updated 21d ago

Evaluation Results

Method	Links
Deep Ensemble 2026.05		16.57	94.09	43.74	0.44
Deep Ensemble 2026.05		16.57	97.55	52.12	0.52
MC Dropout 2026.05		16.66	96.18	49.54	0.5
MC Dropout 2026.05		16.66	98.63	59.03	0.59
J-INN 2026.05		18.35	91.04	43.07	0.86
C-INN 2026.05		18.57	87.95	39.86	1.08
C-INN 2026.05		18.57	94.81	48.23	0.78
MC Dropout 2026.05		19.15	90.86	44.31	0.75
MC Dropout 2026.05		19.15	95.07	52.79	0.94
C-INN 2026.05		19.39	89.75	42.31	1.28
C-INN 2026.05		19.39	95.62	52.23	0.79
Bayesian NN 2026.05		19.6	92.45	46.45	0.51
Bayesian NN 2026.05		19.6	96.65	55.34	0.67
Bayesian NN 2026.05		19.63	87.28	40.39	1.59
Bayesian NN 2026.05		19.63	92.72	48.12	1.54
J-INN 2026.05		19.82	89.2	43.04	0.91
J-INN 2026.05		19.82	95.68	53.15	0.79
J-INN 2026.05		20.15	94.54	56.01	1.61
Deep Ensemble 2026.05		20.81	96.03	55.13	0.55
Deep Ensemble 2026.05		20.81	98.67	65.69	0.66