Comparing neural network training performance between Elixir and Python
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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.
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References · 2
- 2015An Introduction to Convolutional Neural Networkscited by 514
- 2017A Survey of Machine Learning for Big Code and Naturalnesscited by 221
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