A substructure‐aware graph neural network incorporating relation ...

Identifying drug–drug interactions (DDIs) is an important aspect of drug design research, and predicting DDIs serves as a crucial guarantee ...

Liangcheng Dong,Baoming Feng,Zengqian Deng, et al. A substructure‐aware graph neural network incorporating relation features for drug–drug interaction ...

A substructure‐aware graph neural network incorporating relation ...

Identifying drug–drug interactions (DDIs) is an important aspect of drug design research, and predicting DDIs serves as a crucial guarantee for avoiding ...

A substructure‐aware graph neural network incorporating relation ...

... relation embedding on optimizing drug representations. In this work, we propose a substructure‐aware graph neural network incorporating relation features ...

A substructure-aware graph neural network incorporating relation ...

A substructure‐aware graph neural network incorporating relation features (RFSA‐DDI) for DDI prediction, which introduces a directed message passing neural ...

A substructure-aware graph neural network incorporating relation ...

A substructure‐aware graph neural network incorporating relation features for drug–drug interaction prediction. Liangcheng Dong, Baoming Feng, Zengqian Deng ...

Substructure Aware Graph Neural Networks

We propose a novel framework neural network framework called Substructure Aware Graph Neural Networks (SAGNN) to address these issues.

(PDF) STNN-DDI: a Substructure-aware Tensor Neural Network to ...

... relation embedding on optimizing drug representations. In this work, we propose a substructure‐aware graph neural network incorporating relation features ...

SSR-DTA: Substructure-aware multi-layer graph neural networks for ...

... relationships between substructures. Abstract. Accurate ... incorporating sequence-based learning. The concurrent extraction of ...

STNN-DDI: A Substructure-aware Tensor Neural Network to Predict ...

A substructure‐aware graph neural network incorporating relation features (RFSA‐DDI) for DDI prediction, which introduces a directed message passing neural ...

Substructure Aware Graph Neural Networks

Based on the fact that it is easier to distinguish the original graph through subgraphs, we propose a novel framework neural network framework called Sub-.

A Substructure-Aware and High Expressive Graph Neural Network ...

Y Lipman. Incorporating heterophily into graph neural networks for graph classification. W Ye; J Yang; S Medya; A Singh. Nested graph neural ...

Relation Structure-Aware Heterogeneous Graph Neural Network

Existing works on modeling heterogeneous graphs usually follow the idea of splitting a heterogeneous graph into multiple homogeneous subgraphs. This is ...

Structure and position-aware graph neural network for airway labeling

Therefore, an SPGNN layer without positional encodings is a graph attention network layer with a skip connection. ... incorporating positional encoding as ...

Chain-aware graph neural networks for molecular property prediction

AbstractMotivation. Predicting the properties of molecules is a fundamental problem in drug design and discovery, while how to learn ...

Exploiting Mutual Information for Substructure-aware Graph ... - IJCAI

propose an adversarial learning based framework to integrate substructures into GRL ... MI neural estimation on learning graph representations. In this paper, we ...

Knowledge-aware Graph Neural Networks with Label Smoothness ...

ABSTRACT. Knowledge graphs capture structured information and relations between a set of entities or items. As such knowledge graphs repre-.

Relation-aware Graph Convolutional Networks for Multi-relational ...

Following the previous discussion, a key challenge in ERGCN framework is how to incorporate relation embeddings in the convolution function. As the solution, we ...

Affinity-Aware Graph Networks - NIPS papers

We present a means of incorporating these statistics as scalar edge features in a message passing neural network (MPNN) [15] (see Section 3.4). In addition to ...

Improving Graph Neural Network Expressivity via Subgraph...

... aware message passing scheme based on substructure encoding. We show that our architecture allows incorporating domain-specific inductive biases and that it ...