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A curated list of awesome work on VAEs, disentanglement, representation learning, and generative models.

vae variational-autoencoder awesome-list disentanglement disentangled-representations representation-learning deep-learning generative-model unsupervised-learning variational-inference

awesome-vaes's People

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matthewvowels1 avatar talolard avatar

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thunder112358 kasakh bismex paulzhangising spateria bczhu ayankumarbhunia vmishra-uu un-lock-me jianliu-ml yyht moresun zhaoxiaoliang-clh mafrasiabi satyam-cyc arita37 colinsongf atanas1054 talolard batteryhp funkdub baobunuo bolimath daydreamer2023 complexdata lifeworks zhangyu2ustc wazzed deblinaml satpreetsingh rmoraffa shaplacs overbestfitting dragongw whutwuxiaofeng salmankh47 codtan ywu40 kevinwss oucxlw nareshram256 diamondspark marlin-github pragyanaischool aymenbenothman linhlpv absf123 andreajparker yanivboodman shubhangi17002 tgyy1995 adityadutt taolusi avirupju mohsensharifi1991 pankajkarman metalln zyxnlp hanaccount sanyamlakhanpal eunjnnn rongfei-chen anu-bioinfo mxliu dhockaday kee-qin mitchell-xiyunfeng kayla220 hanyangliu 3803531 maroo-sky mamun41 avudzor bbridgecn globle-thunder

awesome-vaes's Issues

Typo on page 3.

This list is awesome! However, I believe there are some mistakes there.
The definition of mutual information on page 3:
image
should be $H_p(z) - H_p(z|x)$ , and you missed log here.

The sourse of the ppt

Thanks for your sharing! I am quite interested in the PPT in the repository and I wanna know if there is a presentation (video) about the PPT?

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