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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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# References
+ [Introduction To Autoencoders In Machine Learning](https://youtu.be/NZ97-lFEUq8)
+ [Convolutional autoencoder for image denoising](https://keras.io/examples/vision/autoencoder/)
+ [B…
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Suggested list of courses would be:
- An introduction to deep learning **
- How to train a neural network
- Regularisation in neural networks
- Deep Bayesian neural networks
- Conv…
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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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# Autoencoders and Diffusers: A Brief Comparison
A quick overview of variational and denoising autoencoders and comparing them to diffusers.
[https://eugeneyan.com/writing/autoencoders-vs-diffusers/…
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https://github.com/L1aoXingyu/pytorch-beginner/blob/61db1de8a2528ab50cd64b50af2268a8b3bc01a4/08-AutoEncoder/Variational_autoencoder.py#L87
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Following models are proposed to be added:
- [x] Adversarial Autoencoders
- [x] ~Adversarial Variational Bayes~
- [ ] ALI/BiGAN
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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
…
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> - “In more uncommon cases in which institutional policies do not permit the sharing of
derived data sets, synthetic data containing the same statistical properties can be generated and shared freel…
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For one-hot-encoding, the list of hybridization choices misses [S-Hybridization](https://www.rdkit.org/docs/source/rdkit.Chem.rdchem.html#rdkit.Chem.rdchem.HybridizationType.S):
https://github.com/Ha…