Row 13474

Row ID: 13474 | Dataset Entry | Axioma AXP Content Repository

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Yeah I think this statement is misleading. Computationally, Equivariant models are actually fairly cheap to evaluate, specifically because they do not need to be that big and are very data efficient. I’ve worked a lot in designing CUDA implementations for these models and they are best in class in terms of accuracy vs. Computational cost.

They are not easy to understand, though, and it can take some time to be comfortable with them if you’re not familiar with group theory.

FieldValue
text Yeah I think this statement is misleading. Computationally, Equivariant models are actually fairly cheap to evaluate, specifically because they do not need to be that big and are very data efficient. I’ve worked a lot in designing CUDA implementations for these models and they are best in class in terms of accuracy vs. Computational cost. They are not easy to understand, though, and it can take some time to be comfortable with them if you’re not familiar with group theory.
label r/machinelearning
dataType comment
communityName r/MachineLearning
datetime 2024-05-20
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{
  "text": "Yeah I think this statement is misleading. Computationally, Equivariant models are actually fairly cheap to evaluate, specifically because they do not need to be that big and are very data efficient. I’ve worked a lot in designing CUDA implementations for these models and they are best in class in terms of accuracy vs. Computational cost. \n\nThey are not easy to understand, though, and it can take some time to be comfortable with them if you’re not familiar with group theory.",
  "label": "r/machinelearning",
  "dataType": "comment",
  "communityName": "r/MachineLearning",
  "datetime": "2024-05-20",
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