This is a pytorch implementation of Associative Domain Adaptation.

Domain adaptation results

val ⬇️, train ➡️	just svhn	just mnist	svhn to mnist	mnist to svhn
svhn	93.9	60.3	95.3	85.6
mnist	59.3	99.4	98.3	99.6

Notes

1. I randomly color MNIST dataset during training and evaluation (see input_pipeline.py).
2. To get "just svhn" and "just mnist" results run train_usual.py.
3. To get "svhn to mnist" and "mnist to svhn" results run train.py.
4. All four networks were trained for 15 epochs with the same hyperparameters.

Training curves

Deep CORAL

Here are results for Deep CORAL: Correlation Alignment for Deep Domain Adaptation.

val ⬇️, train ➡️	svhn to mnist	mnist to svhn
svhn	95.2	61.2
mnist	78.8	99.5

To get these results run train_deep_coral.py.

Requirements

1. pytorch 1.0
2. numpy, Pillow

Other implementations

1. stes/torch-associative
2. haeusser/learning_by_association