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Convolutional Neural Networks Predict Elliptic Curve Ranks

By PulseAugur Editorial · [1 sources] ·

Researchers have applied one-dimensional convolutional neural networks to predict the analytic rank of elliptic curves over the rational numbers. This method, building on prior work by Kazalicki, Vlah, Bujanović, and Novak, demonstrated high accuracy in its predictions across various conductors. The study also explores the relationship between prediction saliency, murmurations, and Mestre--Nagao sums. AI

IMPACT Applies deep learning techniques to number theory, potentially opening new avenues for mathematical research and discovery.

RANK_REASON The cluster contains a research paper published on arXiv detailing a novel application of machine learning to a mathematical problem. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv stat.ML →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

Convolutional Neural Networks Predict Elliptic Curve Ranks

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The cluster contains a research paper published on arXiv detailing a novel application of machine learning to a mathematical problem. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv stat.ML TIER_1 English(EN) · Joanna Bieri, Edgar Costa, Alyson Deines, Kyu-Hwan Lee, David Lowry-Duda, Thomas Oliver, Yidi Qi, Tamara Veenstra ·

    Murmurations, Mestre--Nagao sums, and Convolutional Neural Networks for elliptic curves

    arXiv:2603.17681v2 Announce Type: replace-cross Abstract: We apply one-dimensional convolutional neural networks to the Frobenius traces of elliptic curves over $\mathbb{Q}$ and evaluate and interpret their predictive capacity. In keeping with similar experiments by Kazalicki--Vl…

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