1 code implementation • 3 Sep 2021 • Cristina Cornelio, Sanjeeb Dash, Vernon Austel, Tyler Josephson, Joao Goncalves, Kenneth Clarkson, Nimrod Megiddo, Bachir El Khadir, Lior Horesh
We develop a method to enable principled derivations of models of natural phenomena from axiomatic knowledge and experimental data by combining logical reasoning with symbolic regression.
no code implementations • 11 Jun 2020 • Vernon Austel, Cristina Cornelio, Sanjeeb Dash, Joao Goncalves, Lior Horesh, Tyler Josephson, Nimrod Megiddo
The Symbolic Regression (SR) problem, where the goal is to find a regression function that does not have a pre-specified form but is any function that can be composed of a list of operators, is a hard problem in machine learning, both theoretically and computationally.