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# š Bug
After upgrading PyTorch and Lightning, the accuracy of the `digit_dann` example appears to be incorrect.
## To reproduce
Executing the demo results in incorrect accuracy and loss valuā¦
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https://witheringmaple.github.io/2020/09/21/Unsupervised-Domain-Adaptation-on-Reading-Comprehension/
It's a private blog...
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The domain adaptation classifier in the MUNIT/SPADE codebases (in "utils.py") doesn't work with arbitrary latent vectors.
For example, changing the number of downsampling layers breaks the code
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domain_adaptation.py is not existing , and all the adaptation code does not work, could u please release it?
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https://github.com/kanosawa/anime-face-faster-rcnn-da.pytorch
```
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# Pytorch multi-GPU Faster R-CNN
# Licensed under The MIT License [seā¦
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I got a couple of emails so asking, so, here it is:
In our work "Unsupervised domain adaptation in brain lesion segmentation with adversarial networks" (https://arxiv.org/abs/1612.08894, accepted iā¦
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https://arxiv.org/pdf/1705.10667.pdf
Adversarial learning has been successfully embedded into deep networks to learn transferable features for domain adaptation, which reduce distribution discrepanā¦
leo-p updated
7 years ago
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Hi,
As I don't have any labeled dataset, I'm wondering what is the best way to adapt NLI and Quora to my domain application (Legal Law) :
- only fine-tuning Bert on my specific corpus and then usā¦
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Just as a quick link list, here is a list of ICLR Submissions using the keyword "Domain Adaptation". I guess waiting for the reviews makes sense before including them in the reading list.
# Unsupā¦