Neural Network Research with Wolfram Language: Exploring Non-Differentiable Boolean Functions

Neural Network Research with Wolfram Language: Exploring Non-Differentiable Boolean Functions

Explore cutting-edge neural network research using Wolfram Language in this 29-minute talk. Discover how to leverage advanced language features for rapid prototyping of neural network applications and innovative research ideas. Learn about the development of a novel neural network capable of learning compact non-differentiable Boolean functions. Delve into topics such as relaxations, margin packing, differentiable majority, and hard NetCode. Gain insights into the problem-solving process, implementation techniques, and the impressive results achieved through this innovative approach to Boolean function learning.