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sander.ai
| | proceedings.neurips.cc
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| | jaketae.github.io
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| | In this short post, we will take a look at variational lower bound, also referred to as the evidence lower bound or ELBO for short. While I have referenced ELBO in a previous blog post on VAEs, the proofs and formulations presented in the post seems somewhat overly convoluted in retrospect. One might consider this a gentler, more refined recap on the topic. For the remainder of this post, I will use the terms "variational lower bound" and "ELBO" interchangeably to refer to the same concept. I was heavily inspired by Hugo Larochelle's excellent lecture on deep belief networks.
| | christopher-beckham.github.io
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| | Techniques for label conditioning in Gaussian denoising diffusion models
| | jxmo.io
4.5 parsecs away

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| A primer on variational autoencoders (VAEs) culminating in a PyTorch implementation of a VAE with discrete latents.