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Following models are proposed to be added:
- [x] Adversarial Autoencoders
- [x] ~Adversarial Variational Bayes~
- [ ] ALI/BiGAN
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Hi,
Where can i find the parameter json file. Thanks.
Sean
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Code up a demo of the Variational AutoEncoder for the MNIST data set.
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First, familiarize yourself with the fundamentals that will be relevant to completing this project. The following resources should help you get started with reinforcement learning, deep learning, and …
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@dustinvtran Hi Dustin,
How hard do you think it is to implement the following models in Edwards using the Tensorflow backend?
- Hierarchical variational models
- [Variational Recurrent Neural…
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Why does the Latent Diffusion Model use **variational autoencoders (VAE)** or similar generative models like **VQ-GAN/VAE** for compression instead of using **AutoEncoder (AE)?** If AE can be consider…
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There is a comment on this post addressing it. I'm not sure if my implementation fixes it: https://towardsdatascience.com/variational-autoencoder-demystified-with-pytorch-implementation-3a06bee395ed
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VAE and DAE: basic principles and tools
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I'm having trouble running your code and am getting the following error.
Any thoughts of what might be wrong?
Thanks.
```
$python main.py
....
Extracting MNIST_data/train-images-idx3-ubyte.gz
…
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Hi ZLeopard,
Thank you for providing this code coupled with your paper Simplex Variational Autoencoder!
Just as a quick note, engine/inference.py is empty, could you provide the inference code?…