[PDF][PDF] Theoretical Analysis of the Brain and Artificial Intelligence

F Pedro - Journal of Robotics Spectrum, 2023 - anapub.co.ke
Many articles have expounded on and defended the potential advantages of co-robotics
(cobots), robotics, AI, and quantum computers in the domains of research and development …

Optimizing graph neural network architectures for schizophrenia spectrum disorder prediction using evolutionary algorithms

S Wang, H Tang, R Himeno, J Solé-Casals… - Computer Methods and …, 2024 - Elsevier
Abstract Background and Objective: The accurate diagnosis of schizophrenia spectrum
disorder plays an important role in improving patient outcomes, enabling timely …

Lightweight CNN architecture design for rolling bearing fault diagnosis

L Jiang, C Shi, H Sheng, X Li… - Measurement Science and …, 2024 - iopscience.iop.org
Rolling bearing is a key component of rotating machinery, and its fault diagnosis technology
is very important to ensure the safety of equipment. With the rapid development of deep …

Knowledge-aware evolutionary graph neural architecture search

C Wang, J Zhao, L Li, L Jiao, F Liu, X Liu… - Knowledge-Based …, 2025 - Elsevier
Graph neural architecture search (GNAS) can customize high-performance graph neural
network architectures for specific graph tasks or datasets. However, existing GNAS methods …

Autoddi: drug–drug interaction prediction with automated graph neural network

J Gao, Z Wu, R Al-Sabri, BM Oloulade… - IEEE Journal of …, 2024 - ieeexplore.ieee.org
Drug–drug interaction (DDI) has attracted widespread attention because when incompatible
drugs are taken together, DDI will lead to adverse effects on the body, such as drug …

Automatic graph topology-aware transformer

C Wang, J Zhao, L Li, L Jiao, F Liu… - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
Existing efforts are dedicated to designing many topologies and graph-aware strategies for
the graph Transformer, which greatly improve the model's representation capabilities …

MTAD: multi-layer temporal transaction anomaly detection in ethereum networks with GNN

B Han, Y Wei, Q Wang, FMD Collibus… - Complex & Intelligent …, 2024 - Springer
In recent years, a surge of criminal activities with cross-cryptocurrency trades have emerged
in Ethereum, the second-largest public blockchain platform. Most of the existing anomaly …

Graph neural architecture prediction

J Gao, BM Oloulade, R Al-Sabri, J Chen, T Lyu… - … and Information Systems, 2024 - Springer
Graph neural networks (GNNs) have shown their superiority in the modeling of graph data.
Recently, increasing attention has been paid to automatic graph neural architecture search …

Depth-adaptive graph neural architecture search for graph classification

Z Wu, J Chen, R Al-Sabri, BM Oloulade… - Knowledge-Based Systems, 2024 - Elsevier
In recent years, graph neural networks (GNNs) based on neighborhood aggregation
schemes have become a promising method in various graph-based applications. To solve …

Graph neural architecture search with heterogeneous message-passing mechanisms

Y Wang, J Chen, Q Li, C He, J Gao - Knowledge and Information Systems, 2024 - Springer
In recent years, neural network search has been utilized in designing effective
heterogeneous graph neural networks (HGNN) and has achieved remarkable performance …