An Interactive Visualization Platform for Deep Symbolic Regression

Abstract

Discovering tractable mathematical expressions that best explain a dataset is a long-standing challenge in artificial intelligence. This problem, known as symbolic regression, is relevant when one seeks to generate new physical knowledge and insights. Since practitioners are primarily interested in knowledge generation, the ability to interact with a symbolic regression algorithm would be highly valuable. Thus, we present an interactive symbolic regression framework that allows users not only to configure runs, but also to control the system during training. The interface provides real-time visualization and diagnostics to help guide the user as they control the algorithm on the fly.

Cite

Text

Kim et al. "An Interactive Visualization Platform for Deep Symbolic Regression." International Joint Conference on Artificial Intelligence, 2020. doi:10.24963/IJCAI.2020/763

Markdown

[Kim et al. "An Interactive Visualization Platform for Deep Symbolic Regression." International Joint Conference on Artificial Intelligence, 2020.](https://mlanthology.org/ijcai/2020/kim2020ijcai-interactive/) doi:10.24963/IJCAI.2020/763

BibTeX

@inproceedings{kim2020ijcai-interactive,
  title     = {{An Interactive Visualization Platform for Deep Symbolic Regression}},
  author    = {Kim, Joanne Taery and Kim, Sookyung and Petersen, Brenden K.},
  booktitle = {International Joint Conference on Artificial Intelligence},
  year      = {2020},
  pages     = {5261-5263},
  doi       = {10.24963/IJCAI.2020/763},
  url       = {https://mlanthology.org/ijcai/2020/kim2020ijcai-interactive/}
}