This project investigates the approximation capabilities of Rectified Linear Unit (ReLU) neural networks and compares their performance with classical numerical methods, specifically Finite Element ...

Supports 20+ native Condorcet-like voting methods (extensible), scales from small polls to billions of votes in resource-constrained environments. Rigorously tested and documented.