-
## 0. 論文
https://arxiv.org/abs/1807.01990
Tadanobu Inoue, Subhajit Chaudhury, Giovanni De Magistris, Sakyasingha Dasgupta
## 1. どんなもの?
Synthetic ImageとReal Imageをそれぞれ入力に使い、Variational AutoEncode…
-
Hi, I hope I'm not bothering you. Recently, I have implemented a simple autoencoder with keras for text classification to do domain adaptation, but it performs worse than the original representation o…
-
Exciting work. Love it that you are exploring autoencoders.
I wish this works similarly well with sparse autoencoders, hence the title of the issue.
-
I am very interested at the work in this paper, could you please send me the code?
-
Stateful LSTM, Siamese Network link is broken.
-
**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 …
-
Checked examples are tested to be working with MXNet backend
Not supported examples have clear error message specifying the exact functionality MXNet does not support yet
- [x] addition_rnn.py
…
-
Hi!
I want to run "Junction Tree Variational Autoencoder" on the original dataset used in the paper. I want to use the pre-trained model "JTVAE_ZINC_no_kl" but I don't know how exactly I should use t…
-
Hi, very interesting paper btw!
I'm replicating the code in PyTorch, but noticed that you've not used the `is_training` parameter for one of the layer below. I was wandering if that was intended, si…
-
Hi . I am encountered with some errors.
TypeError: random_normal() got an unexpected keyword argument 'std'
I am wondering if it is related to the environment I was running.
There is no "image_d…