Jun 13, 2024 · We introduce a novel method that enables GNN models to glean insights from these specialized diminutive causal structures, thereby enhancing overall ...
Jun 7, 2024 · We introduce a novel DCSGL method, which enables the GNN model to learn diminutive causal structure that is associated with the graph ...
A novel method for introducing diminutive causal structures into GNN models. Thorough theoretical analysis and substantiation regarding the studied problem.
Jul 9, 2024 · Our method specifically extracts causal knowledge from the model representation of these diminutive causal structures and incorporates ...
Jun 14, 2024 · Our method specifically extracts causal knowledge from the model representation of these diminutive causal structures and incorporates ...
This survey comprehensively review recent research efforts on Causality-Inspired GNNs (CIGNNs) and introduces a taxonomy of CIGNNs based on the type of ...
Jun 14, 2024 · This paper introduces a new method for incorporating diminutive causal structure into graph representation learning. The proposed approach aims ...
Oct 22, 2024 · Recently, one has seen a surge of interest in developing such methods including ones for learning such representations for (undirected) graphs ( ...
Introducing diminutive causal structure into graph representation learning. H Gao, P Qiao, Y Jin, F Wu, J Li, C Zheng. Knowledge-Based Systems 293, 111592, 2024.
Introducing Diminutive Causal Structure into Graph Representation Learning · VoxNeuS: Enhancing Voxel-Based Neural Surface Reconstruction via Gradient ...