4 papers · 1 filter
CITE: A Comprehensive Benchmark for Heterogeneous Text-Attributed Graphs on Catalytic Materials
Chenghao Zhang, Qingqing Long, Ludi Wang +3
Text-attributed graphs(TAGs) are pervasive in real-world systems,where each node carries its own textual features. In many cases these graphs are inherently heterogeneous, containi…
Collaborative Multi-Agent Reinforcement Learning for Automated Feature Transformation with Graph-Driven Path Optimization
Xiaohan Huang, Dongjie Wang, Zhiyuan Ning +7
Feature transformation methods aim to find an optimal mathematical feature-feature crossing process that generates high-value features and improves the performance of downstream ma…
FastFT: Accelerating Reinforced Feature Transformation via Advanced Exploration Strategies
Tianqi He, Xiaohan Huang, Yi Du +6
Feature Transformation is crucial for classic machine learning that aims to generate feature combinations to enhance the performance of downstream tasks from a data-centric perspec…
CataLM: Empowering Catalyst Design Through Large Language Models
Ludi Wang, Xueqing Chen, Yi Du +3
The field of catalysis holds paramount importance in shaping the trajectory of sustainable development, prompting intensive research efforts to leverage artificial intelligence (AI…