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UID:pretalx-juliacon2023-QN3XGU@pretalx.com
DTSTART;TZID=EST:20230728T100000
DTEND;TZID=EST:20230728T103000
DESCRIPTION:Neural networks are typically sensitive to small input perturba
 tions\, leading to unexpected or brittle behaviour. We present RobustNeura
 lNetworks.jl: a Julia package for neural network models that are construct
 ed to naturally satisfy robustness constraints. We discuss the theory behi
 nd our model parameterisation\, give an overview of the package\, and demo
 nstrate its use in image classification\, reinforcement learning\, and non
 linear robotic control.
DTSTAMP:20260515T224512Z
LOCATION:26-100
SUMMARY:Learning smoothly: machine learning with RobustNeuralNetworks.jl - 
 Nicholas Barbara
URL:https://pretalx.com/juliacon2023/talk/QN3XGU/
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