An issue about the official code for DMMIA in "easyrobust/examples/attacks/dmmia_inversion"
- Dominant language
- Jupyter Notebook
- Stars
- 339
- Forks
- 38
- PR merge metrics
- No merged PRs in 30d
Description
Recently, I have tried to reproduce the results presented in the paper "Model Inversion Attack via Dynamic Memory Learning" with the official code in the path "easyrobust/examples/attacks/dmmia_inversion". However, I found that much of the code is conflicted with the paper's description and instead kept the baseline settings of "Plug & Play Attacks: Towards Robust and Flexible Model Inversion Attacks".
I wonder if there is an up-to-date version of the code for DMMIA, whicn may not be uploaded to the repository? I would appreciate it if you could help us with it.
Contributor guide
No contributing guide indexed for this repository
Research direction
Start by inspecting easyrobust/examples/attacks/dmmia_inversion and compare its implementation and settings with the DMMIA paper and the Plug & Play Attacks baseline. The issue names no specific test or entry point; done would require confirming whether an up-to-date DMMIA implementation exists or documenting that the code matches the paper rather than the baseline.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- jupyter-notebook, pytorch
- Domain
- computer-vision, machine-learning, security
- Issue type
- Bug
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 20/100