Pre-training a scalable graph U-net on 20,000 simulated CAD deformations lets it match or beat a from-scratch model on small benchmark datasets, with the paper reporting up to an 11.05% lower position RMSE when fine-tuned on 1/16 of the training data.
Transfer learning with resnet-50 for malaria cell- image classification
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
citation-role summary
background 1
citation-polarity summary
fields
cs.LG 1years
2025 1verdicts
CONDITIONAL 1roles
background 1polarities
background 1representative citing papers
citing papers explorer
-
Transfer learning in Scalable Graph Neural Network for Improved Physical Simulation
Pre-training a scalable graph U-net on 20,000 simulated CAD deformations lets it match or beat a from-scratch model on small benchmark datasets, with the paper reporting up to an 11.05% lower position RMSE when fine-tuned on 1/16 of the training data.