marcoancona/DeepExplain
A unified framework of perturbation and gradient-based attribution methods for Deep Neural Networks interpretability. DeepExplain also includes support for Shapley Values sampling. (ICLR 2018)
PythonMIT
Stargazers
- alex-hh
- anewlearner
- asadabbas09The University of Newcastle
- asross
- baha-m
- cancan101@Free-Agency
- chinakook
- codealphago
- denkorzhMoscow, Russia
- fly51flyPRIS
- gongyanchaoIntel
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- jpzhangvincentSalesforce
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- KeyKy
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- kwanhong66Elice
- liamnaka
- maeglin89273
- marcoanconaMorgen AG
- mikigomKAIST
- nkundiushutiEarth Species Project
- pankracy40i4
- parasdahalUniversity of Amsterdam
- parkerzf
- pramitchoudhary@oidlabs.com
- qyzdaoTencent
- s6junchengGermany
- sameerkhurana10MIT
- sumrania
- sunyiyouUniversity of Wisconsin Madision
- suyogduttjainAustin, TX
- t-davidsonRutgers University
- TomaszRewakOptiver
- valyome
- yulongwang12Beijing, China