MADE: Masked Autoencoder for Distribution Estimation
Paper on arxiv and at ICML2015.
- python = 2.7
- numpy > 1.7
- scipy > 0.11
- theano > 0.6
See python trainMADE.py --help
Experiments are saved in : ./experiments/{experiment_name}/.
Datasets need to be in : ./datasets/{dataset_name}.npz.
Commands to generate the best result from the paper on multiple dataset.
DNA
python -u trainMADE.py dna 1e-5 0.95 -1 -1 Full 300 100 30 False 0 adadelta 0 [500] 1234 False Output False hinge Orthogonal 0
MNIST (Warning: Orthogonal initialization takes a long time and a lot of RAM (4gig) with a model that big.)
python -u trainMADE.py --name mnist_from_paper binarized_mnist 0.01 0 -1 32 Full 300 100 30 False 0 adagrad 0 [8000,8000] 1234 False Output False hinge Orthogonal 0
Generating an X by Y image of MNIST digit sampled from a model (assuming the one above).
python -u sampleMADE.py experiments/mnist_from_paper/ 10 10 True True 1
In repo:
- adult
- connect4
- dna
- mushrooms
- nips
- ocr_letters
- web
External download due to size: