Package with losses for distribution learning
Project description
Histogram Based Losses
This library contains implementations of some histogram-based loss functions:
- Earth Mover Distrance Loss
- Histgramm Loss (paper, original code)
- Inverse Histogram Loss (our impovements)
- Bidirectinal Histogramm Loss (our impovements)
- Continuous Histogram Loss (paper)
Also there are implementations of another losses to compare:
- Negative Log-Likelihood
- Binomial Deviance loss (paper)
Installation
Installation from source
The instalation directly from this repository:
https://github.com/stat-ml/hist-loss.git
cd histloss
python setup.py install
Pip Installation
pip install hist-loss
Example of usage
criterion = HistogramLoss()
positive = torch.sigmoid(torch.randn(10, requires_grad=True))
negative = torch.sigmoid(torch.randn(10, requires_grad=True))
loss = criterion(positive, negative)
loss.backward()
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