When machine learning meets complexity: why Bayesian deep learning is unavoidable

By now, all of you have probably followed deep learning research for quite a while. In 1998, LeCun et al. proposed the very simple MNIST data set of handwritten digits and showed with their LeNet-5 that we can achieve a high validation accuracy on it. The data sets subsequently proposed became more complex (e.g., ImageNet […]