#graph neural networks
82 papers · 1 filter
Learning to Trace Seiberg Dualities
Jonathan J. Heckman, Shani Meynet, Alessandro Mininno +1
The paper applies machine learning, including transformers and MLPs, to identify Seiberg dualities in supersymmetric quiver gauge theories by learning quiver mutations, showing imp…
DualG-MRAG: Decoupling Macro-Reasoning and Micro-Matching for Multimodal Retrieval-Augmented Generation
Jiacheng Tao, Qingyun Sun, Haonan Yuan +2
The paper introduces DualG-MRAG, a framework that separates global reasoning and fine-grained evidence matching using macro and micro graphs to improve multimodal retrieval-augment…
Graph Neural Network Force Fields for Spin Dynamics in Metallic Magnets
Ali Rayat, Yunhao Fan, Gia-Wei Chern
The paper presents a graph neural network framework that learns magnetic force fields from electronic calculations to efficiently simulate spin dynamics in metallic magnets, reprod…
Same Graph Cross-Task Transfer in GNNs: Protocols and Predictors
Neelam Akula, Surbhi Kumar, Murat Kantarcioglu +1
The paper defines a clean evaluation protocol for transferring knowledge between node classification and link prediction on the same graph, shows that transfer is directionally dep…
Graph Neural Multilevel Preconditioners for Iterative Solvers
Zechen Zhang, Rui Peng Li, Yousef Saad
The paper proposes a Graph Neural Multilevel Preconditioner that integrates an algebraic multigrid hierarchy into a learned GNN framework to improve the convergence of iterative so…
Oracle-Budgeted Molecular Optimization with Short-Term Graph Memory
Jiannan Yang, Veronika Thost, Xiang Ling +1
The paper proposes a short-term graph memory module that uses an online graph neural surrogate to pre‑screen candidate molecules, allowing a fixed oracle budget to be spent on high…