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Hi, given an input image tensor x and extracting the glow model i tried the following:
latent = glow(x)[2]
x_reconstructed = glow.reverse(latent)
Since it is a normalizing flow one would expect…
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We are trying to implement the Neural ODE paper as part of the [JAX/FLAX Community Week at Hugging Face](https://discuss.huggingface.co/t/open-to-the-community-community-week-using-jax-flax-for-nlp-cv…
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Hi there!
Thanks for your excellent tutorial on NFs and the code. While playing one the one thing I wanted to do was just generate transformed pdfs and check if they integrate to 1. Using your pla…
vr308 updated
4 years ago
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Hi Edvard,
I need to invert a MAF layer (using another flow function and not an affine one), however I am having issues grasping the concept of it.
So:
1. When training normalizing flows to us…
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Hello,
I was wondering how I can generate samples using the decoder network after training. In a VAE, I would just sample from the prior distribution z~N(0,1) and generate a data point using the de…
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There are various ways this could be done:
* purely from samples. pros: model agnostic, cons: high variance, need to use a kernel method
* using mixture of gaussians: pros: lower variance, cons: ver…
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### 🚀 The feature, motivation and pitch
Dear experts,
I am attempting to export a normalizing flows model built using the Zuko libraries, which are based on PyTorch, to ONNX. However, I am encou…
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1. Why Model-Based?
- It's possible to be more data efficient although model-free might have better asymptotic performance
- Models allow easily injecting inductive biases
2. What about other ge…
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I am trying to compose a Normalizing Flow (Sylvester) with a bijective (Tanh) transform to run the following code:
```py
dim = 2
mu = torch.zeros(dim)
log_std = torch.zeros(dim)
transforms = [dis…
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Hi, I met a cuda runtime error as following:
RuntimeError: svd_cuda: the updating process of SBDSDC did not converge (error: 22)
Recently, I am studying normalizing flow, such as Glow, however, a st…