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VERSION:2.0
PRODID:-//pretalx//pretalx.com//juliacon-2022//talk//MFU9MN
BEGIN:VEVENT
SUMMARY:ExplainableAI.jl: Interpreting neural networks in Julia - Adrian H
 ill
DTSTART:20220728T172000Z
DTEND:20220728T173000Z
DTSTAMP:20260815T163849Z
UID:pretalx-juliacon-2022-MFU9MN@pretalx.com
DESCRIPTION:In pursuit of interpreting black-box models such as deep image
  classifiers\, a number of techniques have been developed that attribute a
 nd visualize the importance of input features with respect to the output o
 f a model.\nExplainableAI.jl brings several of these methods to Julia\, bu
 ilding on top of primitives from the Flux ecosystem. In this talk\, we wil
 l give an overview of current features and show how the package can easily
  be extended\, allowing users to implement their own methods and rules.
LOCATION:Blue
URL:https://pretalx.com/juliacon-2022/talk/MFU9MN/
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