Turnitin
降AI改写
早检测系统
早降重系统
Turnitin-UK版
万方检测-期刊版
维普编辑部版
Grammarly检测
Paperpass检测
checkpass检测
PaperYY检测
[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 …
(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
Abstract Background and Objective: The accurate diagnosis of schizophrenia spectrum
disorder plays an important role in improving patient outcomes, enabling timely …
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 …
is very important to ensure the safety of equipment. With the rapid development of deep …
Knowledge-aware evolutionary graph neural architecture search
Graph neural architecture search (GNAS) can customize high-performance graph neural
network architectures for specific graph tasks or datasets. However, existing GNAS methods …
network architectures for specific graph tasks or datasets. However, existing GNAS methods …
Autoddi: drug–drug interaction prediction with automated graph neural network
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 …
drugs are taken together, DDI will lead to adverse effects on the body, such as drug …
Automatic graph topology-aware transformer
Existing efforts are dedicated to designing many topologies and graph-aware strategies for
the graph Transformer, which greatly improve the model's representation capabilities …
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 …
in Ethereum, the second-largest public blockchain platform. Most of the existing anomaly …
Graph neural architecture prediction
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 …
Recently, increasing attention has been paid to automatic graph neural architecture search …
Depth-adaptive graph neural architecture search for graph classification
In recent years, graph neural networks (GNNs) based on neighborhood aggregation
schemes have become a promising method in various graph-based applications. To solve …
schemes have become a promising method in various graph-based applications. To solve …
Graph neural architecture search with heterogeneous message-passing mechanisms
In recent years, neural network search has been utilized in designing effective
heterogeneous graph neural networks (HGNN) and has achieved remarkable performance …
heterogeneous graph neural networks (HGNN) and has achieved remarkable performance …