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GAN-Trained-Model Detection and Attribution

The implementation of paper Detection and Attribution of Models Trained on Generated Data[^*].

[^*]: Please note that in my published paper, the experiments mentioned to have used the VGG-9 model were actually conducted using the VGG-11 model. I apologize for this error and any confusion it may have caused.

Core symbols most depended-on inside this repo

Shape

Function 2,064
Method 863
Class 307

Languages

Python100%

Modules by API surface

models/GAN_structures.py41 symbols
GANs/model.py41 symbols
Attacks/model.py23 symbols
models/structures/lenet.py20 symbols
models/structures/shufflenetv2.py17 symbols
models/structures/pnasnet.py17 symbols
models/structures/resnet.py16 symbols
models/structures/preact_resnet.py16 symbols
models/structures/densenet.py16 symbols
models/GAN_layers.py16 symbols
models/CIFAR10_model_train_multi_fake_by_backdooring_GAN_singleclass.py16 symbols
models/CIFAR10_model_train_multi_fake_by_backddoring_GAN.py16 symbols

For agents

$ claude mcp add GAN-Trained-Model-Detection-and-Attribution \
  -- python -m otcore.mcp_server <graph>

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