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Author:
None
License:
MIT License
Copyright (c) 2024 Yannik Potdevin
Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated do...
Summary:
A library aiding to create deanonymizers (attacks on privacy preserving machine learning models) for the AnoMed competition platform.
Latest version:
0.0.11
Required dependencies:
adversarial-robustness-toolbox
|
anomed-challenge
|
anomed-utils
|
falcon
|
numpy
|
pandas
|
requests
Optional dependencies:
coverage
|
pytest
|
pytest-cov
|
pytest-mock
|
ruff
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