# Learning Euler Factors of Elliptic Curves

arXiv: https://arxiv.org/abs/2502.10357 · HTML: https://mlsanity.com/paper/2502.10357/

## Key facts

- Cited by 4 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 14 Feb 2025.

## Built on by (most cited first, 4 of 4)

- [From Black Box to Bijection: Interpreting Machine Learning to Build a Zeta Map Algorithm](https://mlsanity.com/paper/2511.12421/) (2025)
- [Int2Int: a framework for mathematics with transformers](https://mlsanity.com/paper/2502.17513/) (2025)
- [Transformers Learn the Mestre-Nagao Heuristic](https://mlsanity.com/paper/2606.15036/) (2026)
- [Decision trees, Frobenius traces, and Weierstrass coefficients of elliptic curves](https://mlsanity.com/paper/2607.24251/) (2026)

## Abstract (arXiv)

We apply transformer models and feedforward neural networks to predict Frobenius traces ap from elliptic curves given other traces aq. We train further models to predict ap bmod 2 from aq bmod 2, and cross-analysis such as ap bmod 2 from aq. Our experiments reveal that these models achieve high accuracy, even in the absence of explicit number-theoretic tools like functional equations of L-functions. We also present partial interpretability findings.