- Kernel tricks: How can purely mathematical approaches beat neural networks in terms of efficiancy? (This is actually an open problem for a long time, you can check Neural Tangent Kernels, Reproducing Kernel Hilbert Spaces for examples and Universal Approximation Property for neural networks )

- I was mainly here for Geometric Deep Learning but another user has already posted it. You should definitely check http://geometricdeeplearning.com . As a mathematician-to-be, I strongly believe that this is the future of ML/DL . Hit me up if you wanna discuss this statement further.