Search Results for author:
Found 4 papers, 2 papers with code
Toward Physically Plausible Data-Driven Models: A Novel Neural Network Approach to Symbolic Regression
Symbolic regression is a method that can automatically generate such models from data.
SymFormer: End-to-end symbolic regression using transformer-based architecture
The task of finding formulas from a set of observed inputs and outputs is called symbolic regression.
Constructing Parsimonious Analytic Models for Dynamic Systems via Symbolic Regression
We demonstrate on a real pendulum system that the analytic model found enables a RL controller to successfully perform the swing-up task, based on a model constructed from only 100 data samples.
Symbolic Regression Methods for Reinforcement Learning
Reinforcement learning algorithms can solve dynamic decision-making and optimal control problems.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
