6 papers
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…
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…
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…
A Novel Paradigm for Neural Computation: X-Net with Learnable Neurons and Adaptable Structure
Yanjie Li, Weijun Li, Lina Yu +14
Multilayer perception (MLP) has permeated various disciplinary domains, ranging from bioinformatics to financial analytics, where their application has become an indispensable face…
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…
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…