Turnitin
降AI改写
早检测系统
早降重系统
Turnitin-UK版
万方检测-期刊版
维普编辑部版
Grammarly检测
Paperpass检测
checkpass检测
PaperYY检测
Understanding and extending subgraph gnns by rethinking their symmetries
Subgraph GNNs are a recent class of expressive Graph Neural Networks (GNNs) which
model graphs as collections of subgraphs. So far, the design space of possible Subgraph …
model graphs as collections of subgraphs. So far, the design space of possible Subgraph …
Universal prompt tuning for graph neural networks
In recent years, prompt tuning has sparked a research surge in adapting pre-trained models.
Unlike the unified pre-training strategy employed in the language field, the graph field …
Unlike the unified pre-training strategy employed in the language field, the graph field …
Rethinking the expressive power of gnns via graph biconnectivity
Weisfeiler and leman go machine learning: The story so far
In recent years, algorithms and neural architectures based on the Weisfeiler-Leman
algorithm, a well-known heuristic for the graph isomorphism problem, have emerged as a …
algorithm, a well-known heuristic for the graph isomorphism problem, have emerged as a …
Substructure aware graph neural networks
Despite the great achievements of Graph Neural Networks (GNNs) in graph learning,
conventional GNNs struggle to break through the upper limit of the expressiveness of first …
conventional GNNs struggle to break through the upper limit of the expressiveness of first …
Sign and basis invariant networks for spectral graph representation learning
We introduce SignNet and BasisNet--new neural architectures that are invariant to two key
symmetries displayed by eigenvectors:(i) sign flips, since if $ v $ is an eigenvector then so is …
symmetries displayed by eigenvectors:(i) sign flips, since if $ v $ is an eigenvector then so is …
Path neural networks: Expressive and accurate graph neural networks
Graph neural networks (GNNs) have recently become the standard approach for learning
with graph-structured data. Prior work has shed light into their potential, but also their …
with graph-structured data. Prior work has shed light into their potential, but also their …
Ordered subgraph aggregation networks
Numerous subgraph-enhanced graph neural networks (GNNs) have emerged recently,
provably boosting the expressive power of standard (message-passing) GNNs. However …
provably boosting the expressive power of standard (message-passing) GNNs. However …