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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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# 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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For example, this can be used as a reference implementation -- https://github.com/lbelzile/TruncatedNormal
Randl updated
4 years ago
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https://arxiv.org/abs/1610.02415v1
Directly related to #52 and #53. Somewhat related to #45, #55, and #56. This preprint examines an autoencoder-based method for representing molecules with continuou…
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Graph generative models are important for the tasks we have been describing.
The core idea is to posit a model which defines some distribution over graphs ```P(G)```, for instance via a low dimensi…
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Dear Sir,
I'm really sorry. I don't know how to contact you via email so I write this on your GitHub.
How are you? I haven't seen your new post on Medium. I hope you are doing well.
I just rea…
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https://jakevdp.github.io/PythonDataScienceHandbook/04.08-multiple-subplots.html
**Linear Regression Derivation**
https://towardsdatascience.com/linear-regression-derivation-d362ea3884c2
**ASS*…
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![image](https://user-images.githubusercontent.com/1320252/125286221-243f1400-e34e-11eb-81ba-20228537e208.png)
Appetizer for 3D, Neural rendering with GAN, GIRAFFE, CVPR2021 best paper
- https://a…
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Post a reading of your own that uses deep learning for social science analysis and understanding, with a focus on network, graph, or tabular data.