tensorflow / tensorflow/probability
KL-reweighting not done correctly in BNN code ?
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Description
Hi,
It seems that there is some discrepancy in how the KL-reweighting is done
during stochastic/batched training.
In section 3.4 of this paper: Weight Uncertainty in Neural Networks, the KL divergence is re-weighted using "number of batches", but in the BNN example code here, the KL divergence is re-weighted using size of batch
Does this seem like a bug ?
Thanks
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Research direction
Read section 3.4 of the linked Weight Uncertainty in Neural Networks paper, then inspect the Bayesian neural network example at the referenced line in tensorflow_probability/examples/bayesian_neural_network.py. Compare the KL reweighting factors used for stochastic or batched training and determine whether the example matches the paper; done means resolving whether the discrepancy is a bug.
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Assessment
- Tech stack
- python, tensorflow
- Domain
- machine-learning
- Issue type
- Bug
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Stale
- Clarity
- Mostly clear
- Newbie friendliness
- 35/100