I was able able to run the code perfectly but the hyperparameters given for mTAN-full do not achieve 0.858 AUROC on physionet2012. The highest is AUROC ~0.827 with AUPRC ~0.45.
This is achieved with this command:
python3 tan_classification.py --alpha 100 --niters 300 --lr 0.0001 --batch-size 50 --rec-hidden 256 --gen-hidden 50 --latent-dim 20 --enc mtan_rnn --dec mtan_rnn --n 8000 --quantization 0.016 --save 1 --classif --norm --kl --learn-emb --k-iwae 1 --dataset physionet
I was able able to run the code perfectly but the hyperparameters given for mTAN-full do not achieve 0.858 AUROC on physionet2012. The highest is AUROC ~0.827 with AUPRC ~0.45.
This is achieved with this command:
python3 tan_classification.py --alpha 100 --niters 300 --lr 0.0001 --batch-size 50 --rec-hidden 256 --gen-hidden 50 --latent-dim 20 --enc mtan_rnn --dec mtan_rnn --n 8000 --quantization 0.016 --save 1 --classif --norm --kl --learn-emb --k-iwae 1 --dataset physionet