The subgraph agglomeration results on the Graph-SST2 dataset with a GCN graph classifier. All instances all correctly predicted. Red is negative and blue is ... |
dig.xgraph.dataset - Dive into Graphs Documentation diveintographs.readthedocs.io › latest › dataset
The dataset Graph-SST2 should be downloaded to the proper directory before running. All the three datasets Graph-SST2, Graph-SST5, and Graph-Twitter can ... |
This repository contains the official implementation of GSAT as described in the paper: Interpretable and Generalizable Graph Learning via Stochastic Attention ... |
Despite the recent progress in Graph Neural Networks (GNNs), it remains challenging to explain the predictions made by GNNs. Existing explanation methods ... |
Official code of "Discovering Invariant Rationales for Graph Neural Networks" (ICLR 2022) - Wuyxin/DIR-GNN. ... Graph-SST2: this dataset can be downloaded here. |
The Stanford Sentiment Treebank is a corpus with fully labeled parse trees that allows for a complete analysis of the compositional effects of sentiment in ... |
Meanwhile, our model consistently performs better than GIN and GCN on both OGDB and Graph-SST2. Among them, SGR gains a 4.98% improvement over GIN and 6.94% ... |
11 февр. 2023 г. · Graph-SST2 (OOD) is a manually regrouped dataset, where the graphs are split into different sets according to the average node degrees. |
[PDF] Enhancing Uncertainty Quantification and Interpretability with ... proceedings.mlr.press › ...
Graph-SST2 is a sentiment analysis dataset, where each text sequence in SST2 is converted to a graph. Following the splits in the study of Wu et al. [2022b], ... |
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