C&EN

Improving Compound Activity Classification via Deep Transfer and Representation Learning

Department of Computer Science and Engineering, The Ohio State University, Columbus, Ohio 43210, United States Biomedical Informatics, The Ohio State University, Columbus, Ohio 43210, United States ...
IEEE

LMTCSG: Multilabel Text Classification Combining Sequence-Based and GNN-Based Features

Abstract: Since multilabel text classification datasets often face the problem of label imbalance, therefore, using either sequence-based deep learning (DL) model or graph neural network (GNN)-based ...
IEEE

BGNN-TC: BERT GNN Based Text Classification Algorithm

Abstract: The traditional Text-Level-GNN effectively captures the structural information of texts but fails to fully extract the semantic information of words during text-level composition. To address ...
GitHub

microsoft/tf2-gnn: TensorFlow 2 library implementing Graph Neural Networks

Implementation and example training scripts of various flavours of graph neural network in TensorFlow 2.0. Much of it is based on the code in the tf-gnn-samples repo. The code is maintained by the ...
Frontiers

A Multi-Task Representation Learning Architecture for Enhanced Graph Classification

Composed of nodes and edges, graph structured data are organized in the non-Euclidean geometric space and ubiquitous especially in chemical compounds, proteins, etc. They usually contain rich ...