This repository implements the antialiased CNN technique from the ICML 2019 paper ‘Making Convolutional Networks Shift-Invariant Again’. It provides a BlurPool layer that replaces standard downsampling operations in CNNs to reduce aliasing artifacts. The library includes pretrained antialiased versions of common architectures (ResNet, VGG, DenseNet, ResNeXt, Wide ResNet) that achieve better stability and accuracy on image classification tasks. Users can either load pretrained models directly or integrate the BlurPool layer into their own custom architectures.