mlsanityData to 14 Oct 2026

Comparing neural network training performance between Elixir and Python

arXiv 2210.13945 ↗First posted 25 Oct 2022cs.LG cs.PLcited by 0

Not on the map. Why?

Abstract (arXiv)

With a wide range of libraries focused on the machine learning market, such as TensorFlow, NumPy, Pandas, Keras, and others, Python has made a name for itself as one of the main programming languages. In February 2021, Jos'e Valim and Sean Moriarity published the first version of the Numerical Elixir (Nx) library, a library for tensor operations written in Elixir. Nx aims to allow the language be a good choice for GPU-intensive operations. This work aims to compare the results of Python and Elixir on training convolutional neural networks (CNN) using MNIST and CIFAR-10 datasets, concluding that Python achieved overall better results, and that Elixir is already a viable alternative.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 2 of its 9 references that are in the map. First posted on arXiv 25 Oct 2022.

Builds on

2 of 9 references.

References · 2

  1. 2015An Introduction to Convolutional Neural Networkscited by 514
  2. 2017A Survey of Machine Learning for Big Code and Naturalnesscited by 221

Built on by

Not cited yet.