Body: <p>I want to build a model that when given two vectors, outputs the probability of one vector being the encoded form of the other. I have 2 strategies for this: (<strong>Dataset available</strong>)</p>
  <ol>
  <li><p>I can directly feed them in concatenation to a neural network and take the output as the probability.</p>
  </li>
  <li><p>I can train a conditional GAN with the conditional vector being the encoded vector and using the original vector as the generated one. In this case, the discriminator works as the network that I train in the first approach.</p>
  </li>
  </ol>
  <p>Which approach is better? Am I thinking in the right direction?</p>
  
Comments.ContentLicense: CC BY-SA 4.0
Comments.CreationDate: 2021-04-27T04:46:14.003Z
Comments.Text: I haven't dealt with vector encodings, but I would suggest changing the title of your post to be more relevant. Maybe something like "What model best suits vector encoding classification"
Comments.UserDisplayName: Recessive
Comments.ContentLicense: CC BY-SA 4.0
Comments.CreationDate: 2021-04-27T08:58:59.793Z
Comments.Text: Okayy! I'll do that
Comments.UserDisplayName: Aditya Abhiram
Tags: <neural-networks><generative-adversarial-networks><models>
Title: Which approach best suits vector encodings?
UserDisplayName: Aditya Abhiram
ThreadText: # Which approach best suits vector encodings?
  
  (Asked by: username_0 on 2021-04-27)
  
  I want to build a model that when given two vectors, outputs the probability of one vector being the encoded form of the other. I have 2 strategies for this: (**Dataset available**)
  
  1. I can directly feed them in concatenation to a neural network and take the output as the probability.
  2. I can train a conditional GAN with the conditional vector being the encoded vector and using the original vector as the generated one. In this case, the discriminator works as the network that I train in the first approach.
  
  Which approach is better? Am I thinking in the right direction?
  
  **Tags:** neural-networks, generative-adversarial-networks, models
  > **Comments:**
  > **username_1**: I haven't dealt with vector encodings, but I would suggest changing the title of your post to be more relevant. Maybe something like "What model best suits vector encoding classification"  
  > **username_0**: Okayy! I'll do that  
  
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  ## 0 answers
  
  