The code requires Python 3.7 or later. The file requirements.txt contains the full list of required Python modules.
- Interpolation Task on Toy Dataset
python3 tan_interpolation.py --niters 5000 --lr 0.0001 --batch-size 128 --rec-hidden 32 --latent-dim 1 --length 20 --enc mtan_rnn --dec mtan_rnn --n 1000 --gen-hidden 50 --save 1 --k-iwae 5 --std 0.01 --norm --learn-emb --kl --seed 0 --num-ref-points 20 --dataset toy
- Interpolation Task on PhysioNet Dataset
python3 tan_interpolation.py --niters 500 --lr 0.001 --batch-size 32 --rec-hidden 64 --latent-dim 16 --quantization 0.016 --enc mtan_rnn --dec mtan_rnn --n 8000 --gen-hidden 50 --save 1 --k-iwae 5 --std 0.01 --norm --learn-emb --kl --seed 0 --num-ref-points 64 --dataset physionet --sample-tp 0.9
- Classification Task on PhysioNet Dataset (mTAND-Full)
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
- Classification Task on PhysioNet Dataset (mTAND-Enc)
python3 tanenc_classification.py --niters 200 --lr 0.0001 --batch-size 128 --rec-hidden 128 --enc mtan_enc --n 8000 --quantization 0.016 --save 1 --classif --num-heads 1 --learn-emb --dataset physionet --seed 0
- Classification Task on MIMIC-III Dataset (mTAND-Full)
python3 tan_classification.py --alpha 5 --niters 300 --lr 0.0001 --batch-size 128 --rec-hidden 256 --gen-hidden 50 --latent-dim 128 --enc mtan_rnn --dec mtan_rnn --save 1 --classif --norm --learn-emb --k-iwae 1 --dataset mimiciii
For MIMIC-III Dataset, first you need to have an access to the dataset which can be requested here. We follow the data extraction process described here: https://github.com/mlds-lab/interp-net.
- Classification Task on MIMIC-III Dataset (mTAND-Enc)
python3 tanenc_classification.py --niters 200 --lr 0.0001 --batch-size 256 --rec-hidden 256 --enc mtan_enc --quantization 0.016 --save 1 --classif --num-heads 1 --learn-emb --dataset mimiciii --seed 0
- Classification Task on Human Activity Dataset (mTAND-Enc)
python3 tanenc_classification.py --niters 1000 --lr 0.001 --batch-size 256 --rec-hidden 512 --enc mtan_enc_activity --quantization 0.016 --save 1 --classif --num-heads 1 --learn-emb --dataset activity --seed 0 --classify-pertp