Sequential Image Classification on MNIST ordered pixel-by-pixel 1.0 (test)
98.8AccuracyNRNN
Evaluation Results
| Method | Links | |
|---|---|---|
| NRNNAdversarial perturbation radius (r)=0.01, Perturbation type=FGSM, Hidden dimension (dh)=128, Training multiplicative noise=0.02, Training additive noise=0.022021.02 | 98.8 | |
| NRNNAdversarial perturbation radius (r)=0.01, Perturbation type=FGSM, Hidden dimension (dh)=128, Training multiplicative noise=0.02, Training additive noise=0.052021.02 | 98.8 | |
| Lipschitz RNNAdversarial perturbation radius (r)=0.01, Perturbation type=FGSM, Hidden dimension (dh)=1282021.02 | 98.1 | |
| coRNNAdversarial perturbation radius (r)=0.01, Perturbation type=FGSM, Hidden dimension (dh)=1282021.02 | 97.5 | |
| coRNN# units=128, Number of parameters=34k2021.10 | 96.6 | |
| LEM# units=128, Number of parameters=68k2021.10 | 96.6 | |
| Lipschitz RNN# units=128, Number of parameters=34k2021.10 | 96.3 | |
| expRNN# units=360, Number of parameters=69k2021.10 | 96.2 | |
| anti.sym. RNN# units=128, Number of parameters=10k2021.10 | 95.8 | |
| NRNNAdversarial perturbation radius (r)=0.05, Perturbation type=FGSM, Hidden dimension (dh)=128, Training multiplicative noise=0.02, Training additive noise=0.052021.02 | 95.5 | |
| chrono-LSTM# units=128, Number of parameters=68k2021.10 | 94.6 | |
| Exponential RNNAdversarial perturbation radius (r)=0.01, Perturbation type=FGSM, Hidden dimension (dh)=1282021.02 | 94.5 | |
| NRNNAdversarial perturbation radius (r)=0.05, Perturbation type=FGSM, Hidden dimension (dh)=128, Training multiplicative noise=0.02, Training additive noise=0.022021.02 | 94.3 | |
| GRU# units=256, Number of parameters=201k2021.10 | 94.1 | |
| LSTM# units=256, Number of parameters=267k2021.10 | 92.9 | |
| NRNNAdversarial perturbation radius (r)=0.1, Perturbation type=FGSM, Hidden dimension (dh)=128, Training multiplicative noise=0.02, Training additive noise=0.052021.02 | 86.8 | |
| Lipschitz RNNAdversarial perturbation radius (r)=0.05, Perturbation type=FGSM, Hidden dimension (dh)=1282021.02 | 85.7 | |
| coRNNAdversarial perturbation radius (r)=0.05, Perturbation type=FGSM, Hidden dimension (dh)=1282021.02 | 85.5 | |
| NRNNAdversarial perturbation radius (r)=0.1, Perturbation type=FGSM, Hidden dimension (dh)=128, Training multiplicative noise=0.02, Training additive noise=0.022021.02 | 79.6 | |
| Antisymmetric RNNAdversarial perturbation radius (r)=0.01, Perturbation type=FGSM, Hidden dimension (dh)=1282021.02 | 79.4 | |
| NRNNAdversarial perturbation radius (r)=0.15, Perturbation type=FGSM, Hidden dimension (dh)=128, Training multiplicative noise=0.02, Training additive noise=0.052021.02 | 70.6 | |
| Exponential RNNAdversarial perturbation radius (r)=0.05, Perturbation type=FGSM, Hidden dimension (dh)=1282021.02 | 59.3 | |
| Lipschitz RNNAdversarial perturbation radius (r)=0.1, Perturbation type=FGSM, Hidden dimension (dh)=1282021.02 | 58.9 | |
| NRNNAdversarial perturbation radius (r)=0.15, Perturbation type=FGSM, Hidden dimension (dh)=128, Training multiplicative noise=0.02, Training additive noise=0.022021.02 | 58.3 | |
| coRNNAdversarial perturbation radius (r)=0.1, Perturbation type=FGSM, Hidden dimension (dh)=1282021.02 | 55.9 | |
| Lipschitz RNNAdversarial perturbation radius (r)=0.15, Perturbation type=FGSM, Hidden dimension (dh)=1282021.02 | 37.1 | |
| coRNNAdversarial perturbation radius (r)=0.15, Perturbation type=FGSM, Hidden dimension (dh)=1282021.02 | 35.1 | |
| Antisymmetric RNNAdversarial perturbation radius (r)=0.05, Perturbation type=FGSM, Hidden dimension (dh)=1282021.02 | 24.7 | |
| Exponential RNNAdversarial perturbation radius (r)=0.1, Perturbation type=FGSM, Hidden dimension (dh)=1282021.02 | 19.7 | |
| Exponential RNNAdversarial perturbation radius (r)=0.15, Perturbation type=FGSM, Hidden dimension (dh)=1282021.02 | 14.3 | |
| Antisymmetric RNNAdversarial perturbation radius (r)=0.1, Perturbation type=FGSM, Hidden dimension (dh)=1282021.02 | 11.4 | |
| Antisymmetric RNNAdversarial perturbation radius (r)=0.15, Perturbation type=FGSM, Hidden dimension (dh)=1282021.02 | 10.2 |