BatchNorm wins the Test-of-Time Award at #ICML2025! 🎉 BatchNorm revolutionized deep learning by addressing internal covariate shift, which can slow down learning, limits learning rates, and makes it difficult to train deep networks. By normalizing inputs within each mini-batch, BatchNorm significantly stabilized and accelerated training. It enabled higher learning rates, improved gradient flow, and paved the way for much deeper architectures like ResNet. Beyond reducing internal covariate shift, BatchNorm also smooths the optimization landscape and improves model generalization, making it a cornerstone of modern neural network training. Very well deserved, @Sergey_xai and @ChrSzegedy!