# The minimal width of universal p-adic ReLU neural networks

arXiv: https://arxiv.org/abs/2603.00064 · HTML: https://mlsanity.com/paper/2603.00064/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 4 of its 7 references that are in the map.
- First posted on arXiv 10 Feb 2026.

## Builds on (most cited first, 4 of 4)

- [The Expressive Power of Neural Networks: A View from the Width](https://mlsanity.com/paper/1709.02540/) (2017)
- [Approximating Continuous Functions by ReLU Nets of Minimal Width](https://mlsanity.com/paper/1710.11278/) (2017)
- [Minimum Width for Universal Approximation](https://mlsanity.com/paper/2006.08859/) (2020)
- [Minimum width for universal approximation using ReLU networks on compact domain](https://mlsanity.com/paper/2309.10402/) (2023)

## Abstract (arXiv)

We determine the minimal width of p-adic neural networks with the universal approximation property for continuous mathbb Qp-valued functions on compact open subsets with respect to the Lq norms and the C1 norm, where the activation function is a natural p-adic analogue of the ReLU function.