83 datasets found

MUTAG, NCI1, PTC, PROTEINS, IMDB-BINARY and IMDB-MULTI datasets are graph classification datasets.

The paper discusses the use of multi-objective Bayesian optimization for hyperparameter transfer in topic models.

The dataset used in the paper is NAS-Bench-101, a benchmark for neural architecture search.

The dataset used in the paper is ENAS Macro, a search space for neural architecture search.

The dataset used in the paper is RandWire, a randomly wired neural network search space.

A critical aspect of Graph Neural Networks (GNNs) is to enhance the node representations by aggregating node neighborhood information. However, when detecting anomalies, the...

Graph Neural Networks (GNNs) are versatile, powerful machine learning methods that enable graph structure and feature representation learning, and have applications across many...

Node classification is the task of predicting the labels of unlabeled nodes in a graph. State-of-the-art methods based on graph neural networks achieve excellent performance...

Multimodal Spatiotemporal Graph-Transformer for Hospital Readmission Prediction

Deep Graph Neural Networks (GNNs) are useful models for graph classification and graph-based regression tasks. In these tasks, graph pooling is a critical ingredient by which...

Knowledge graphs store a wealth of knowledge from the real world into structured graphs, which consist of collections of triplets, and each triplet (h, r, t) represents that...

Pitfalls of graph neural network evaluation

Click-Through Rate (CTR) prediction plays a core role in recommender systems, serving as the final-stage filter to rank items for a user. The key to addressing the CTR task is...

The Flixster dataset is a collection of user-item interactions.

The Yahoo! Music dataset is a collection of user-item interactions.

MovieLens-100K and MovieLens-1M datasets are used for performance testing of comparative experiments.

Matrix completion has been formulated as the link prediction problem on a bipartite user-item graph in recent GNN-based matrix completion methods.

Graph classification and node classification datasets

Graph classification and node classification datasets

Graph classification and node classification datasets