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Hi, thank you for sharing your source code.
Could you please give more explanation why do you need the potential normalization, the only description about it that I can find in your paper is the following,
Potential normalization (PN) is simple: we normalize the scores s to an empirical distribution of zero mean and one variance. The difference with batch-norm (BN) is that we apply PN at an instance-level, rather than a batch-level.
But I am still confused about what it is for. It's just for numerical stability?
And is the following the implementation of potential normalization?
Hi, thank you for sharing your source code.
Could you please give more explanation why do you need the potential normalization, the only description about it that I can find in your paper is the following,
But I am still confused about what it is for. It's just for numerical stability?
And is the following the implementation of potential normalization?
Partially-Observed-TreeCRFs/tree_crf_layer.py
Lines 100 to 104 in c4040eb
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