[R] Towards White Box Deep Learning

I present a conceptual framework for building inherently interpretable neural networks. The PoC 4-layer model for a subproblem of MNIST can be considered a White Box: the decision boundary is easily explainable and the model is robust to adversarial attacks - despite no form of adversarial training!

The approach essentially reduces to a general idea of how to share weights inside a network layer to achieve highly interpretable and robust features. Its general nature and effectiveness suggest that it should …

adversarial adversarial attacks adversarial training attacks box building decision deep learning form framework general layer machinelearning mnist networks neural networks poc robust training