Row 10126

Row ID: 10126 | Dataset Entry | Axioma AXP Content Repository

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Interestingly, there was more invariance baked into the AlphaFold 2 model (in particular they defined an invariant point attention mechanism) that they got rid of in AlphaFold 3. In AlphaFold 3 it is more implicit - while training the diffusion module, they "create 48 versions of the input structure by randomly rotating and translating and adding independent noise to each structure".

I would be curious how it performs if I add back more invariance rather than have the model try to learn it implicitly - thanks for the link to e3nn, seems like an interesting starting point!

FieldValue
text Interestingly, there was more invariance baked into the AlphaFold 2 model (in particular they defined an invariant point attention mechanism) that they got rid of in AlphaFold 3. In AlphaFold 3 it is more implicit - while training the diffusion module, they "create 48 versions of the input structure by randomly rotating and translating and adding independent noise to each structure". I would be curious how it performs if I add back more invariance rather than have the model try to learn it impl…
label r/machinelearning
dataType comment
communityName r/MachineLearning
datetime 2024-05-20
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  "text": "Interestingly, there was more invariance baked into the AlphaFold 2 model (in particular they defined an invariant point attention mechanism) that they got rid of in AlphaFold 3. In AlphaFold 3 it is more implicit - while training the diffusion module, they \"create 48 versions of the input structure by randomly rotating and translating and adding independent noise to each structure\".\n\nI would be curious how it performs if I add back more invariance rather than have the model try to learn it implicitly - thanks for the link to e3nn, seems like an interesting starting point!",
  "label": "r/machinelearning",
  "dataType": "comment",
  "communityName": "r/MachineLearning",
  "datetime": "2024-05-20",
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