Abstract: This letter proposes a pose-graph attentional graph neural network, called P-GAT, which compares (key)nodes between sequential and non-sequential sub-graphs for place recognition tasks as ...

Learn how Network in Network (NiN) architectures work and how to implement them using PyTorch. This tutorial covers the concept, benefits, and step-by-step coding examples to help you build better ...

Accurate prediction of protein-protein interactions (PPIs) is crucial for understanding cellular functions and advancing the development of drugs. While existing in-silico methods leverage direct ...

The fusion of artificial neural networks (NNs) with photonics has generated significant implications across various scientific fields and industries. A new tutorial review published in the journal ...

Abstract: A Graph Neural Network (GNN) conducts the graph convolution for structured data and obtains the weighted sum over the vertices according to its graph structure. However, in the context of a ...

All experiments were performed in Python 3.8 with Pytorch (v1.10). prep_eggnet_data_protcid_model.py --dir many_xtal --label 0 --threshold 12 --skip_filter prep_eggnet_data_protcid_model.py --dir many ...

ABSTRACT: Most modern face recognition and classification systems mainly rely on hand-crafted image feature descriptors. In this paper, we propose a novel deep learning algorithm combining ...