ansk

7 ms·

1. 61.▲
   by ansk 6y ago

   I glanced over the paper and it appears that the generative model used for cifar-5m wasn't even trained with a proper train/test split. It was simply trained until the FID on the training set stopped decreasing. That's a pr
2. 62.▲
   by ansk 6y ago

   Question for someone knowledgable about this: if I have a model which is large -- but small enough that I can fit a single training example on GPU -- does this approach offer speedups compared to simple gradient accumulation? Or is this on
3. 63.▲
   by ansk 6y ago

   About a month ago, OpenAI released information on their latest project -- a neural network which aims to generate images from text[1]. The results were impressive and the work received a lot of attention in the ML community. The repo link
4. 64.▲
   by ansk 6y ago

   It can be as deterministic as you want it to be -- there are parameters that control how much randomness is used during the sampling process. Finding the most probable sequence from the learned distribution is intractable for all but the s
5. 65.▲
   by ansk 6y ago

   If you look at the latest research in neural network based approaches to text-to-speech, you'll find plenty of examples of realistic synthetic voices. However, due to the nature of the available training data (audiobooks), these model