Related Issues (17)
- Final Loss equation HOT 12
- some questions about formulation 10 in paper
- uncertainty for self-supervised learning HOT 1
- This is a lucky demo When I change the data generation process, the prediction of the variance is wrong HOT 2
- Question about the loss
- Log var can become negative and explode HOT 1
- Why return torch.mean(loss)? HOT 1
- How can I use the trained model for prediction? is it right to use prediction_model.predict(new_x) ? HOT 2
- log_var_a and log_var_b
- Code Doesn't Agree with Paper HOT 1
- about σ HOT 1
- MergeLoss with regular item is \log_{sigma} in paper but \log_{sigma}^2 in code HOT 3
- The loss might be nagative value HOT 11
- Any way to incorporate these methods in other tasks easily? HOT 7
- Question on relative weights
- Sounds like a lucky result comes from a wrong formula deduction HOT 2
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from multi-task-learning-example.