Interactive Symbolic Regression - A Study on Noise Sensitivity and Extrapolation Accuracy
Author:
Affiliation:
1. Amrita Vishwa Vidyapeetham, Coimbatore, India
2. Amrita Vishwa Vidyapeetham University, Coimbatore, India
Publisher
ACM
Link
https://dl.acm.org/doi/pdf/10.1145/3638530.3664130
Reference29 articles.
1. S. Akshay, K. P. Soman, Neethu Mohan, and S. Sachin Kumar. 2021. Dynamic Mode Decomposition and Its Application in Various Domains: An Overview. Springer International Publishing, Cham, 121--132.
2. Operon C++
3. SRBench Competition. 2022. Retrieved April 06 2024 from https://cavalab.org/srbench/competition-2022/
4. Miles Cranmer. 2020. Pysr: Fast & parallelized symbolic regression in python/julia. Zenodo, September (2020).
5. Laure Crochepierre Lydia Boudjeloud-Assala and Vincent Barbesant. 2022. Interactive Reinforcement Learning for Symbolic Regression from Multi-Format Human-Preference Feedbacks.. In IJCAI. 5900--5903.
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