Warped Cross Entropy

This project explores an alternative to standard categorical cross-entropy by mapping classes to optimized unit vectors in a lower-dimensional space, rather than using sparse one-hot encoding. Tested on MNIST, the "Warped Cross Entropy" approach achieved comparable accuracy (96.39%) to standard methods while utilizing significantly fewer dimensions in the final layer. For more details on my other work, check out my blog post about this.