Row 47876

Row ID: 47876 | Dataset Entry | Axioma AXP Content Repository

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Alright so I have a tensor that I get from doing a fluid simulation. The "image" in this case is a mesh with for each point the value of the pressure, x velocity, y velocity, extra stress ... These dimensions I use as channels currently and I need a CNN to do feature extraction. I am a bit confused however on whether I should use conv2d or conv3d. Which would be best?

Some insight on this would be much appreciated!

FieldValue
text Alright so I have a tensor that I get from doing a fluid simulation. The "image" in this case is a mesh with for each point the value of the pressure, x velocity, y velocity, extra stress ... These dimensions I use as channels currently and I need a CNN to do feature extraction. I am a bit confused however on whether I should use conv2d or conv3d. Which would be best? Some insight on this would be much appreciated!
label r/deeplearning
dataType post
communityName r/deeplearning
datetime 2024-05-22
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Raw Record

{
  "text": "Alright so I have a tensor that I get from doing a fluid simulation. The \"image\" in this case is a mesh with for each point the value of the pressure, x velocity, y velocity, extra stress ... These dimensions I use as channels currently and I need a CNN to do feature extraction. I am a bit confused however on whether I should use conv2d or conv3d. Which would be best?\n\nSome insight on this would be much appreciated!",
  "label": "r/deeplearning",
  "dataType": "post",
  "communityName": "r/deeplearning",
  "datetime": "2024-05-22",
  "username_encoded": "Z0FBQUFBQm5Lak1SM0FMLVVsNWdYZFZ0ZzBGREVUNHdWTGM4YVdLOC1faDh5cUVfY3VZYTl0eXhCcHZ6RlhZUzI0QS0zR3Mtd0lJR3VIWW1OUTltMUxVYVNCT2JOZjVBV1A5QV9LQ0dDQVN3bHh3Ql9tVE9GWUk9",
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}
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