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The purpose of an activation layer is to add some non-linearity to the network. This allows expressing much more complex tasks with our networks. But...

Two brains are better than one. ยท A linear layer takes a set of inputs, and for each node in its layer it sums weights*inputs to calculate the node...

I wanted to try implementing previous work nn + polynomial solvers against a larger problem, in this case MNIST. For anyone hopping in here, I'm...

In the previous attempt, a polynomial based neural network was setup and we had some inconsistent results coming back. My assumption at that point was...

This approach doesn't seem to produce good results. The idea is to create a neural network completely from polynomials (doesn't really require much),...

I'm interested in generative design, especially geometric deep learning. For a simple environment I'd like to have an environment where given some...