Core Machine Learning
NLP
Learning advanced mathematical computations from examples
May 3, 2021
Abstract
Using transformers over large generated datasets, we train models to learn mathematical properties of differential systems, such as local stability, be- havior at infinity and controllability. We achieve near perfect prediction of qualitative characteristics, and good approximations of numerical features of the system. This demonstrates that neural networks can learn to per- form complex computations, grounded in advanced theory, from examples, without built-in mathematical knowledge.
AUTHORS
Written by
François Charton
Amaury Hayat
Guillaume Lample
Publisher
ICLR 2021
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