1 citations · 2 across the 4 of their papers we have counts for
10 papers
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…
ChatSR: Multimodal Large Language Models for Scientific Formula Discovery
Yanjie Li, Lina Yu, Weijun Li +6
Current multimodal large language models (MLLMs) are mainly focused on the understanding and processing of perceptual modalities such as images and videos, while their capability f…
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…
MMSR: Symbolic Regression is a Multi-Modal Information Fusion Task
Yanjie Li, Jingyi Liu, Weijun Li +6
Mathematical formulas are the crystallization of human wisdom in exploring the laws of nature for thousands of years. Describing the complex laws of nature with a concise mathemati…
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…