Neural Discrete Representation Learning · HackerPapers discussions

Neural Discrete Representation Learning — mentioned by stonelazy

Fri, 09 May 2025 01:37:08 GMT

> I don't believe that phonemes are real I used to think the same until I came across the VQ-VAE paper [1], where the goal was to let the model learn the smallest units of speech without any supervision. Interestingly, the model ended up learning units that closely aligned with the phonemes we recognize today. [1] - https://arxiv.org/pdf/1711.00937

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Neural Discrete Representation Learning — mentioned by GistNoesis

Mon, 09 Dec 2024 20:46:35 GMT

If you want to know what tokens you want to obtain _exactly_ Mona Lisa, or any other image, you take the image and put it through your image tokenizer aka encode it, and if you have the sequence of token you can decode it to an image. VQ-VAE (Vector Quantised-Variational AutoEncoder), (2017) https://arxiv.org/abs/1711.00937 The whole encoding-decoding process is reversible, and you only lose some imperceptible "details", the process can be either trained with a L2Loss, or a perceptual loss depending what you value. The point being that images which occurs naturally are not really information…

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Neural Discrete Representation Learning — HN submission

Mon, 06 Nov 2017 16:49:42 GMT

Neural Discrete Representation Learning [pdf]

2 points; 0 discussion replies on HN. Paper and source history. A submission is not an endorsement.