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Objective: Uncover the generative model behind these data samples
1. Assumption 1: The latent states can be uncovered from the principal modes of app usage behavior.
Test:
- [x] PCA dimensional…
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Dear @tkipf,
I really appreciate your work and I would like to adapt your code to my own use cases. In particular, I would like to generate new graphs by sampling from a learned latent space, as usua…
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>We present the DeepProfile framework, which learns a variational autoencoder (VAE) network from thousands of publicly available gene expression samples and uses this network to encode a low-dimension…
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This is just a motivational message 👍
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Thank you for sharing!!
I found that you get `color_image` through bluring :
`batch_colors = np.array([self.imageblur(ba,True) for ba in batch]) / 255.0`
Bluring is a good way to get color prio…
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你这个代码没有用注意力机制啊
01acd updated
11 months ago
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* 논문제목 : SimTS: Rethinking Contrastive Representation Learning for Time Series Forecasting
* 분야 : time series
* 논문 링크 : https://arxiv.org/pdf/2303.18205.pdf
* 발표 자료 : https://cottony-wedelia-967.no…
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beta-VAE is also very good ref : http://openreview.net/forum?id=Sy2fzU9gl
Learning an interpretable factorised representation of the independent data gen- erative factors of the world without super…
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## Abstract
- propose Vector Quantised Variational AutoEncoder (VQ-VAE)
- generative model that learns discrete representations
- prior is learnt rather than static
- solves the issue of "po…