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Operator Feature Neural Network for Symbolic Regression
Yusong Deng, Min Wu, Lina Yu +4
Symbolic regression is a task aimed at identifying patterns in data and representing them through mathematical expressions, generally involving skeleton prediction and constant opt…
DN-CL: Deep Symbolic Regression against Noise via Contrastive Learning
Jingyi Liu, Yanjie Li, Lina Yu +6
Noise ubiquitously exists in signals due to numerous factors including physical, electronic, and environmental effects. Traditional methods of symbolic regression, such as genetic…
Closed-form Solutions: A New Perspective on Solving Differential Equations
Shu Wei, Yanjie Li, Lina Yu +8
The quest for analytical solutions to differential equations has traditionally been constrained by the need for extensive mathematical expertise. Machine learning methods like gene…
Generative Pre-Trained Transformer for Symbolic Regression Base In-Context Reinforcement Learning
Yanjie Li, Weijun Li, Lina Yu +6
The mathematical formula is the human language to describe nature and is the essence of scientific research. Finding mathematical formulas from observational data is a major demand…
Discovering Mathematical Formulas from Data via GPT-guided Monte Carlo Tree Search
Yanjie Li, Weijun Li, Lina Yu +6
Finding a concise and interpretable mathematical formula that accurately describes the relationship between each variable and the predicted value in the data is a crucial task in s…
MetaSymNet: A Tree-like Symbol Network with Adaptive Architecture and Activation Functions
Yanjie Li, Weijun Li, Lina Yu +6
Mathematical formulas serve as the means of communication between humans and nature, encapsulating the operational laws governing natural phenomena. The concise formulation of thes…