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[New Model] <Ma2025Adversarial> #213

@theSleepyPig

Description

@theSleepyPig

Paper Information

  • Paper Title: Adversarial Robustness via Deformable Convolution with Stochasticity
  • Paper URL: https://openreview.net/pdf?id=vISiVCssVg
  • Paper authors: Yanxiang Ma, Zixuan Huang, Minjing Dong, Shan You, Chang Xu

Leaderboard Claim(s)

Add here the claim for your model(s). Copy and paste the following subsection for the number of models you want to add.

Model 1 (CIFAR-100)

  • Architecture: WideResNet34-10
  • Threat Model: Linf
  • eps: 0.03137254901960784
  • Clean accuracy: 66.9
  • Robust accuracy: 46.54
  • Additional data: false
  • Evaluation method: AutoAttack
  • Checkpoint and code: checkpoint code
    json

Model 2 (CIFAR-100)

  • Architecture: ResNet18
  • Threat Model: Linf
  • eps: 0.03137254901960784
  • Clean accuracy: 64.59
  • Robust accuracy: 43.85
  • Additional data: false
  • Evaluation method: AutoAttack
  • Checkpoint and code: checkpoint code
    json

Model 3 (CIFAR-10)

  • Architecture: WideResNet34-10
  • Threat Model: Linf
  • eps: 0.03137254901960784
  • Clean accuracy: 90.58
  • Robust accuracy: 68.39
  • Additional data: false
  • Evaluation method: AutoAttack
  • Checkpoint and code: checkpoint code
    json

Model 4 (CIFAR-10)

  • Architecture: ResNet18
  • Threat Model: Linf
  • eps: 0.03137254901960784
  • Clean accuracy: 89.24
  • Robust accuracy: 67.56
  • Additional data: false
  • Evaluation method: AutoAttack
  • Checkpoint and code: checkpoint code
    json

Model Zoo:

  • I want to add my models to the Model Zoo (check if true)
  • I use an architecture that is included among
    those here or in timm. If not, I added the link to the architecture implementation so that it can be added.
  • I agree to release my model(s) under MIT license (check if true) OR under a custom license, located here: (put the custom license URL here if a custom license is needed. If no URL is specified, we assume that you are fine with MIT)

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