151 citations · 472 across the 49 of their papers we have counts for
9 papers · 1 filter
From Score to Diagnosis: Search-Independent Post-Diagnosis for Symbolic Regression
Qian Li, Yuxiao Hu, Juncheng Liu +2
Symbolic regression (SR) solvers employ diverse search mechanisms, yet most rely on the same low-information scalar fitness. Such scores provide little guidance on why a skeleton f…
Beyond Equation Search: Conjecture-Guided Discovery with SCOPE and ClosureBench
Yuxiao Hu, Qian Li, Ding Wang +4
Most symbolic regression methods optimize candidate equations, but improving an equation's fit does not establish whether its underlying scientific conjecture should be retained, r…
Learning to Design SR Solvers: Harness Optimization for Symbolic Regression
Qian Li, Yuxiao Hu, Qihao Duan +2
Symbolic regression (SR) seeks explicit equations that explain observed data, and recent methods increasingly employ large language models (LLMs) and agents for equation discovery.…
DASS: A Solver-Adaptable Dynamic Auxiliary Search Strategy for Symbolic Regression
Yuxiao Hu, Qian Li, Ding Wang +3
Symbolic regression (SR) aims to discover interpretable mathematical expressions from data and plays a key role in scientific discovery. However, existing methods face a common bot…
Constructed regional photovoltaic generation fields improve ultra-short-term distributed solar forecasting
Dayin Chen, Xiaodan Shi, Xin Xu +5
Ultra-short-term forecasting of densely distributed photovoltaic (PV) systems remains challenging because external meteorological and satellite products may not adequately resolve…
Joint discovery of governing partial differential equations from multi-source datasets by competitive optimization
Hao Xu, Siyu Lou, Yuntian Chen +1
Discovering governing equations directly from observational data is a key step towards interpretable scientific machine learning. Current data-driven approaches typically operate o…
Data-driven discovery of governing differential equations across physical systems
Siyu Lou, Hao Xu, Wenguan Wang +6
Differential equations play a critical role in scientific discovery because they provide a mathematical framework to describe the behaviour of physical phenomena. As a promising al…
CityTrajBench: A Unified Benchmark for City-Scale Vehicle Trajectory Generation
Shibo Zhu, Xiaodan Shi, Dayin Chen +4
Urban trajectory generation is a fundamental task for transportation simulation, urban planning, and mobility analytics. However, systematic comparison across trajectory generation…
Graph-based data-driven discovery of interpretable laws governing corona-induced noise and radio interference for high-voltage transmission lines
Hao Xu, Yuntian Chen, Chongqing Kang +1
The global shift towards renewable energy necessitates the development of ultrahigh-voltage (UHV) AC transmission to bridge the gap between remote energy sources and urban demand.…