Supplementary Materials for FeCAM: Exploiting the Heterogeneity of Class Distributions in Exemplar-Free Continual Learning

Since the Resnet-18 feature extractor uses a ReLU activation function, the feature representation values are all non-negative, so the inputs to tukey's ladder of powers transformation are all valid. As expected, the performance of both methods drops a bit when the pre-training is not done on the similar classes. Still FeCAM outperforms NCM by about 10% on the final accuracy. In Algorithm 1, we present the pseudo code for using FeCAM classifier.Algorithm 1 FeCAM Require: Training data (D