• Lipschitz RNN (--model LipschitzRNN)
• Antisymmetric RNN (--model asymRNN)
• Cayley RNN (--model calRNN)
• Residual RNN (--model resRNN)
• Vanilla RNN: (--model RNN)

Here is an example ro run the Lipschitz RNN on the ordered pixel-by-pixel MNIST classification task:

python3 driver.py --name mnist --model LipschitzRNN --T 784 --n_units 128 --epochs 100 --eps 0.03 --lr 0.003 --lr_decay 0.1 --lr_decay_epoch 90 --beta 0.75 --gamma 0.001 --seed 1

Here is an example ro run the Lipschitz RNN on the permuted pixel-by-pixel MNIST classification task:

python3 driver.py --name pmnist --model LipschitzRNN --T 784 --n_units 128 --epochs 100 --eps 0.03 --lr 0.0035 --lr_decay 0.1 --lr_decay_epoch 90 --beta 0.75 --gamma 0.001 --seed 1

https://arxiv.org/pdf/2006.12070.pdf