Learning with Differentiable Algorithms — mentioned by awesomeMilou

Wed, 28 May 2025 22:35:52 GMT

> What's the innovation here? > Having a distribution to pick from? As I understand it, it's exactly this. Specifically, representing neurons in a neural network via a probability distribution of logic gates and then collapsing the distribution into the optimal logic gate for a given neuron via hyper-parameter tuning in the form of gradient descent. The author has a few more details in their thesis: https://arxiv.org/abs/2209.00616 Specifically it's the training approach that's patented. I'm glad to see that people are trying to improve on his method, so the patent will likely become…

Paper and discussion history. A mention is not an endorsement.

Learning with Differentiable Algorithms · HackerPapers discussions

Learning with Differentiable Algorithms — mentioned by awesomeMilou