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**Description**
Code Embeddings are abstract representations of source code employed in multiple automation tasks in software engineering like clone detection, traceability, or code generation. This …
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Мини блог о курсовой работе.
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https://github.com/facebookresearch/disentangling-correlated-factors
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beta-VAE is also very good ref : http://openreview.net/forum?id=Sy2fzU9gl
Learning an interpretable factorised representation of the independent data gen- erative factors of the world without super…
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Hi Clément,
Thanks for creating and maintaining this great repo. I'm a biostatistician working on environmental epidemiology (meaning that I'm new to machine learning and my questions may be naive)…
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### Metadata
- Authors: Christopher P. Burgess, Irina Higgins, +4 authors Alexander Lerchner
- Organization: DeepMind
- Publish Date: 2018.04
- Paper: https://arxiv.org/pdf/1804.03599.pdf
- 3rd-p…
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> Autoencoders provide a powerful framework for learning compressed representations
by encoding all of the information needed to reconstruct a data point in
a latent code. In some cases, autoencoder…
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[The format of the issue]
Paper name/title:
Project link:
Paper link:
Code link:
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Hello,
Firstly, just wanted to state that this is a great repo with a very understandable code base!
I seem to be getting extremely low MIG / AAM scores (around 1e-3 to 1e-2) when training with …
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Working to align code to VASA white paper
https://github.com/johndpope/VASA-1-hack/blob/main/Net.py
I cherry picked some code from here - which I believe builds off the MegaPortraits stuff
htt…