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Feb 19, 2024 · This approach can potentially generate new principles or insights by discovering generalizable patterns hidden in high-dimensional data.
Feb 19, 2024 · Here we introduce deep distilling, a machine learning method that does not perform searches but instead learns from data using symbolic essence ...
This repository includes code to produce results in the paper "Automated discovery of algorithms from data", which can be read at https://rdcu.be/dy2Go.
My amateur take on this: This paper makes me think of the underlying premise of perceptrons -- the universal approximation theorem -- which states that a ...
Automated discovery of algorithms from data - ResearchGate
www.researchgate.net › publication › 37...
Feb 19, 2024 · Here we introduce deep distilling, a machine learning method that does not perform searches but instead learns from data using symbolic essence ...
Feb 20, 2024 · Nature Computational Science - Automated algorithm discovery has been difficult for artificial intelligence given the immense search space ...
Deep distilling is introduced, a machine learning method that does not perform searches but instead learns from data using symbolic essence neural networks ...
Feb 20, 2024 · - Discovering principles from data: Finally, deep distilling shows how AI can generate and discover complex but human-understandable patterns, ...
(1) The document introduces a new machine learning method called "deep distilling" that learns from data using neural networks called "symbolic essence neural ...
Our work uses genetic programming [27; 5; 55] , and more generally, evolutionary computation [15; 20] . This field provides multiple algorithms but relatively ...