Summary of Research and Implementation Of Data Enhancement Techniques For Graph Neural Networks, by Jingzhao Gu (1) et al.
Research and Implementation of Data Enhancement Techniques for Graph Neural Networksby Jingzhao Gu, Haoyang HuangFirst…
Research and Implementation of Data Enhancement Techniques for Graph Neural Networksby Jingzhao Gu, Haoyang HuangFirst…
The Heterophilic Snowflake Hypothesis: Training and Empowering GNNs for Heterophilic Graphsby Kun Wang, Guibin Zhang,…
Graph Knowledge Distillation to Mixture of Expertsby Pavel Rumiantsev, Mark CoatesFirst submitted to arxiv on:…
A Benchmark for Maximum Cut: Towards Standardization of the Evaluation of Learned Heuristics for Combinatorial…
On GNN explanability with activation rulesby Luca Veyrin-Forrer, Ataollah Kamal, Stefan Duffner, Marc Plantevit, CĂ©line…
Analysing the Behaviour of Tree-Based Neural Networks in Regression Tasksby Peter Samoaa, Mehrdad Farahani, Antonio…
Global-Local Graph Neural Networks for Node-Classificationby Moshe Eliasof, Eran TreisterFirst submitted to arxiv on: 16…
Graph Neural Reaction Diffusion Modelsby Moshe Eliasof, Eldad Haber, Eran TreisterFirst submitted to arxiv on:…
Graph Neural Thompson Samplingby Shuang Wu, Arash A. AminiFirst submitted to arxiv on: 15 Jun…
A Unified Graph Selective Prompt Learning for Graph Neural Networksby Bo Jiang, Hao Wu, Ziyan…