1 citations · 1 across the 6 of their papers we have counts for
8 papers
LLM-PDESR: Robust PDE Discovery via Subdomain Weighted Residuals and LLM-Guided Symbolic Hypothesis Generation
Jinyang Du, Hao Ma, Xiaohu Shi +4
Discovering governing partial differential equations (PDEs) from noisy observational data is a fundamental challenge in scientific machine learning. Traditional symbolic regression…
WeCon: An Efficient Weight-Conditioned Neural Solver for Multi-Objective Combinatorial Optimization Problems
Xuan Wu, Jinbiao Chen, Yang Li +7
Existing neural solvers for Multi-Objective Combinatorial Optimization Problems (MOCOPs) commonly adopt decomposition-based strategies that scalarize a MOCOP into multiple subprobl…
Neural Combinatorial Optimization Algorithms for Solving Vehicle Routing Problems: A Comprehensive Survey with Perspectives
Xuan Wu, Di Wang, Lijie Wen +6
Although several surveys on Neural Combinatorial Optimization (NCO) solvers specifically designed to solve Vehicle Routing Problems (VRPs) have been conducted, they did not cover t…
Troublemaker Learning for Low-Light Image Enhancement
Yinghao Song, Zhiyuan Cao, Wanhong Xiang +5
Low-light image enhancement (LLIE) restores the color and brightness of underexposed images. Supervised methods suffer from high costs in collecting low/normal-light image pairs. U…
Incorporating Surprisingly Popular Algorithm and Euclidean Distance-based Adaptive Topology into PSO
Xuan Wu, Jizong Han, Di Wang +9
While many Particle Swarm Optimization (PSO) algorithms only use fitness to assess the performance of particles, in this work, we adopt Surprisingly Popular Algorithm (SPA) as a co…
Neural Architecture Search based on Cartesian Genetic Programming Coding Method
Xuan Wu, Linhan Jia, Xiuyi Zhang +4
Neural architecture search (NAS) is a hot topic in the field of automated machine learning and outperforms humans in designing neural architectures on quite a few machine learning…