IEEE

A Convolution Bias-Incorporated Nonnegative Latent Factorization of Tensors Model for Accurate Representation Learning to Dynamic Directed Graphs

Abstract: A dynamic directed graph (DDG) can describe complex dynamic interactions among massive entities, for example, traffic transmissions in a metropolitan area network (MAN), in a natural way.
IEEE

A Flexible Diffusion Convolution for Graph Neural Networks

Abstract: Graph Neural Networks (GNNs) have been gaining more attention due to their excellent performance in modeling various graph-structured data. However, most of the current GNNs only consider ...
Scientific Research Publishing

An In-Depth Analysis of Graph Neural Networks and Machine Learning Approaches for Drug Repositioning ()

1 Department of Computer Science and Engineering, Kishoreganj University, Kishoreganj, Bangladesh. 2 Department of Electrical and Computer Engineering, North South University, Dhaka, Bangladesh. 3 ...
Microsoft

Crystal Graph Convolutional Neural Networks for an Accurate and Interpretable Prediction of Material Properties.

The use of machine learning methods for accelerating the design of crystalline materials usually requires manually constructed feature vectors or complex transformation of atom coordinates to input ...