主题图谱 / graph

graph

GeneTech 知识引擎共收录 97 篇相关科研实体，横跨 16 个垂直领域。数据来自 OpenAlex、arXiv、Crossref、PubMed、Europe PMC 等公开学术源，全部可溯源到原文。

年度产出趋势

代表性文献（按质量分排序，前 60 条）

• LLM-enabled multi-agent framework for natural language interaction with graph-based digital twins
  2026 · AI Agent 生态 · Digital twins are increasingly used in the Architecture, Engineering, and Construction (AEC) industry, but their adoption is often hindered by the need for specialised knowledge, such as database querying. This paper pre…
• Cerebrovascular Imaging-to-Graph Reconstruction for Individualized Digital Twin Brains
  2026 · 数字孪生 · ABSTRACT The development of digital twins in medicine, i.e., virtual replicas of human organs, offers a promising path toward precision medicine by enabling interpretable, mechanistic, and actionable insights. In the bra…
• Additional Material for the paper A Self-Adaptive Digital Twin Architecture for Dynamic Resource Management
  2026 · 数字孪生 · Additional Material for the paper A Self-Adaptive Digital Twin Architecture for Dynamic Resource Management The repository contains additional material for the SEAMS 2026 conference paper.The material includes: The sourc…
• Additional Material for the paper A Self-Adaptive Digital Twin Architecture for Dynamic Resource Management
  2026 · 数字孪生 · Additional Material for the paper A Self-Adaptive Digital Twin Architecture for Dynamic Resource Management The repository contains additional material for the SEAMS 2026 conference paper.The material includes: The sourc…
• SYNERGY+
  2026 · 生命科学 · SYNERGY+ is the successor of SYNERGY, a free and open dataset on study selection in systematic reviews. When using this dataset, please cite the accompanying preprint: <blockquote> van der Kuil, T., Westerbeek, E.,…
• HEAL-KGGen: A Hierarchical Multi-Agent LLM Framework with Knowledge Graph Enhancement for Genetic Biomarker-Based Medical Diagnosis
  2025 · AI Agent 生态 · ABSTRACT The discovery and validation of genetic biomarkers across diverse diseases demand intelligent systems capable of integrating complex multi-omics data with clinical relevance. We introduce HEAL-KGGen, an end-to-e…
• AI modeling for outbreak prediction: A graph-neural-network approach for identifying vancomycin-resistant enterococcus carriers
  2025 · AI 安全与对齐 · The isolation of affected patients and intensified infection control measures are used to prevent nosocomial transmission of vancomycin-resistant enterococci (VRE), but early detection of VRE carriers is needed. However,…
• Identifying key genetic variants in Alzheimer’s disease progression using Graph Convolutional Networks (GCN) and biological impact analysis
  2025 · 生物计算 · Abstract Alzheimer’s disease (AD) involves complex genetic interactions that remain challenging to model computationally. We present a novel deep learning framework integrating Single Nucleotide Polymorphism (SNP) data w…
• Atomic-level interpretable multimodal graph neural network for predicting carbon dioxide adsorption in metal-organic frameworks
  2025 · 碳中和与 CCUS · Metal–organic frameworks (MOFs) are porous crystalline materials with strong potential for CO₂ capture because their structures and chemistries are highly tunable. However, their vast compositional and structural search …
• BiDGCNLLM: A Graph–Language Model for Drone State Forecasting and Separation in Urban Air Mobility Using Digital Twin-Augmented Remote ID Data
  2025 · 碳中和与 CCUS · Accurate prediction of drone motion within structured urban air corridors is essential for ensuring safe and efficient operations in Urban Air Mobility (UAM) systems. Although real-world Remote Identification (Remote ID)…
• Rethinking traffic prediction in Mobile Network Digital Twins: A flexible inductive graph-based learning model for data-scarce scenarios
  2025 · 数字孪生 · Network Digital Twins (NDTs) are increasingly relying on data-driven approaches for modeling complex network dynamics. Traffic forecasting is crucial for NDTs to provide timely insights for automated network reconfigurat…
• Enhancing clinical outcome predictions through effective sample size evaluation in graph-based digital twin modeling
  2025 · 数字孪生 · Digital twins in healthcare offer an innovative approach to precision diagnosis, prognosis, and treatment. SynTwin, a novel computational methodology to generate digital twins using synthetic data and network science, ha…
• Digital twin system for manufacturing processes based on a multi-layer knowledge graph model
  2025 · 数字孪生 · Abstract Digital twin technology in the manufacturing process faces challenges like integrating diverse data sources and managing real-time data flow. To address this, we propose a novel three-layer knowledge graph archi…
• MetalMind: A knowledge graph-driven human-centric knowledge system for metal additive manufacturing
  2025 · 数字孪生 · Abstract In the Industry 5.0 era, increasing manufacturing complexity and fragmented knowledge pose challenges for decision-making and workforce development. To tackle this, we present a human-centric knowledge system th…
• Novel Federated Graph Contrastive Learning for IoMT Security: Protecting Data Poisoning and Inference Attacks
  2025 · 隐私计算与数据要素 · Malware evolution presents growing security threats for resource-constrained Internet of Medical Things (IoMT) devices. Conventional federated learning (FL) often suffers from slow convergence, high communication overhea…
• Empowering Federated Graph Rationale Learning with Latent Environments
  2025 · 隐私计算与数据要素 · The success of Graph Neural Networks (GNNs) in graph classification has heightened interest in explainable GNNs, particularly through graph rationalization. This method aims to enhance GNNs explainability by identifying …
• FedMDKGE: Multi-granularity Dynamic Knowledge Graph Embedding in Federated Learning
  2025 · 隐私计算与数据要素 · As knowledge is time-sensitive, some researchers have started to focus on dynamic knowledge graphs to provide time-dimensioned knowledge content thus reflecting richer information. But they have not yet combined temporal…
• Deterministic and reconfigurable graph state generation with a single solid-state quantum emitter
  2025 · 量子计算 · Measurement-based quantum computing offers a promising route towards scalable, universal photonic quantum computation. This approach relies on the deterministic and efficient generation of photonic graph states in which …
• An efficient intelligent transportation system for traffic flow prediction using meta-temporal hyperbolic quantum graph neural networks
  2025 · 量子材料 · Intelligent Transportation Systems (ITS) necessitate scalable, real-time, and adaptive traffic flow prediction models to enhance urban mobility and alleviate congestion. Conventional Graph Neural Network methodologies en…
• Jumping knowledge graph attention network for resource allocation in wireless cellular system
  2025 · 6G 与卫星互联网 · Next-generation wireless networks are characterized by two essential features: ubiquitous connectivity and high-speed data transmission. The realization of these features hinges on the development of rational resource al…
• KG4Diagnosis: A Hierarchical Multi-Agent LLM Framework with Knowledge Graph Enhancement for Medical Diagnosis
  2024 · AI Agent 生态 · Integrating Large Language Models (LLMs) in healthcare diagnosis demands systematic frameworks that can handle complex medical scenarios while maintaining specialized expertise. We present KG4Diagnosis, a novel hierarchi…
• GALA: Graph Diffusion-Based Alignment With Jigsaw for Source-Free Domain Adaptation
  2024 · AI 安全与对齐 · Source-free domain adaptation is a crucial machine learning topic, as it contains numerous applications in the real world, particularly with respect to data privacy. Existing approaches predominantly focus on Euclidean d…
• HAIChart: Human and AI Paired Visualization System
  2024 · AI 安全与对齐 · The growing importance of data visualization in business intelligence and data science emphasizes the need for tools that can efficiently generate meaningful visualizations from large datasets. Existing tools fall into t…
• An interpretable deep learning framework for classifying neuronal morphologies using topology and graph neural networks
  2024 · AI 安全与对齐 · Abstract Neuronal shape determines how neurons process and integrate information, yet a consistent and objective classification of neuronal morphologies remains elusive. Current approaches rely heavily on subjective expe…
• Leveraging Medical Knowledge Graphs Into Large Language Models for Diagnosis Prediction: Design and Application Study
  2024 · 医疗人工智能 · BACKGROUND: Electronic health records (EHRs) and routine documentation practices play a vital role in patients' daily care, providing a holistic record of health, diagnoses, and treatment. However, complex and verbose EH…
• CKG: Improving ABSA with text augmentation using ChatGPT and knowledge-enhanced gated attention graph convolutional networks
  2024 · 仿生智能 · Aspect-level sentiment analysis (ABSA) is a pivotal task within the domain of neurorobotics, contributing to the comprehension of fine-grained textual emotions. Despite the extensive research undertaken on ABSA, the limi…
• Global Trends in Oliceridine (TRV130) Research from 2013 to 2024: A Bibliometrics and Knowledge Graph Analysis
  2024 · 脑科学 · Purpose: The adverse effects and drug abuse issues associated with opioid drugs have made finding a safe and effective alternative a focus of research. Oliceridine has attracted attention for its lower adverse reactions,…
• Conceptual Model of Graph-based Individual Tree and Its Utilization in Digital Twin and Metaverse of Urban Forest
  2024 · 数字孪生 · Abstract. 3D city models are an important cornerstone in the development of digital twin cities, allowing for various analyses and simulations. CityGML, as an open standard for 3D city models, emphasizes five main aspect…
• From data to action in flood forecasting leveraging graph neural networks and digital twin visualization
  2024 · 数字孪生 · Forecasting floods encompasses significant complexity due to the nonlinear nature of hydrological systems, which involve intricate interactions among precipitation, landscapes, river systems, and hydrological networks. R…
• Knowledge Graph-Based Framework to Support Human-Centered Collaborative Manufacturing in Industry 5.0
  2024 · 数字孪生 · The importance of highly monitored and analyzed processes, linked by information systems such as knowledge graphs, is growing. In addition, the integration of operators has become urgent due to their high costs and from …
• Similarity-navigated graph neural networks for node classification
  2023 · AI 安全与对齐 · Graph Neural Networks are effective in learning representations of graph-structured data. Some recent works are devoted to addressing heterophily, which exists ubiquitously in real-world networks, breaking the homophily …
• Deep Learning with Graph Convolutional Networks: An Overview and Latest Applications in Computational Intelligence
  2023 · 医疗人工智能 · Convolutional neural networks (CNNs) have received widespread attention due to their powerful modeling capabilities and have been successfully applied in natural language processing, image recognition, and other fields. …
• LGGNet: Learning From Local-Global-Graph Representations for Brain–Computer Interface
  2023 · 仿生智能 · Neuropsychological studies suggest that co-operative activities among different brain functional areas drive high-level cognitive processes. To learn the brain activities within and among different functional areas of th…
• Scene Graph Contrastive Learning for Embodied Navigation
  2023 · 具身智能 · Training effective embodied AI agents often involves expert imitation, specialized components such as maps, or leveraging additional sensors for depth and localization. Another approach is to use neural architectures alo…
• Pairing-based graph neural network for simulating quantum materials
  2023 · 量子材料 · We develop a pairing-based graph neural network for simulating quantum many-body systems. Our architecture augments a BCS-type geminal wavefunction with a generalized pair amplitude parameterized by a graph neural networ…
• Mortal Runtime Ai Alignment
  2026 · AI 安全与对齐 · This paper provides a rigorous mathematical formalization of the three core algorithmic systems constituting the Mortal Runtime: the ABP (Alignment‑Behavior‑Purpose) geometric‑mean alignment gate, the Chrysalis full‑spec…
• Mortal Runtime Ai Alignment
  2026 · AI 安全与对齐 · This paper provides a rigorous mathematical formalization of the three core algorithmic systems constituting the Mortal Runtime: the ABP (Alignment‑Behavior‑Purpose) geometric‑mean alignment gate, the Chrysalis full‑spec…
• Thermodynamics-Informed Graph Learning for Predicting CO2 Solubility in Water and Multicomponent Brines
  2026 · 碳中和与 CCUS · Abstract Accurate prediction of CO2 solubility in saline water is essential for estimating dissolution trapping in carbon capture, utilization, and storage projects. Although recent gradient-boosting models achieve high …
• 3D Semantic Digital Twins: Data Streams and Ontologies for Risk Prediction in Heritage Contexts
  2026 · 数字孪生 · Abstract. Sensor data are core for real-time monitoring in heritage contexts, allowing to ground the synchronization between the real asset and its Digital Twin (DT). Such synchronization can then be leveraged to perform…
• Multi-View Graph Anomaly Detection Robustness Under View Dropout and Metattack Perturbations
  2026 · 隐私计算与数据要素 · This report synthesises findings from 3 peer-reviewed papers addressing the following research question: What is the impact of view dropout on the robustness of multi-view graph anomaly detection frameworks against Metat…
• Multi-View Graph Anomaly Detection Robustness Under View Dropout and Metattack Perturbations
  2026 · 隐私计算与数据要素 · This report synthesises findings from 3 peer-reviewed papers addressing the following research question: What is the impact of view dropout on the robustness of multi-view graph anomaly detection frameworks against Metat…
• The Convergence of Federated Learning, Knowledge Graphs, and Large Language Models for Language Learning: A Scoping Review
  2026 · 隐私计算与数据要素 · Large Language Models (LLMs) in Intelligent Computer-Assisted Language Learning enable highly personalized learning, yet raise significant challenges related to pedagogical grounding, data privacy, and instructional vali…
• Time and Memory Trade-Offs in Shortest-Path Algorithms Across Graph Topologies: A*, Bellman–Ford, Dijkstra, AI-Augmented A* and a Neural Baseline
  2025 · AI 安全与对齐 · This study presents a comparative evaluation of Dijkstra’s algorithm, A*, Bellman-Ford, AI-Augmented A* and a neural AI-based model for shortest-path computation across diverse graph topologies, with a focus on time effi…
• A Digital Twin Framework for Bridge Structural Health Monitoring with Physics-Informed Graph Networks
  2025 · 数字孪生 · The aging of global infrastructure necessitates advanced methodologies for real-time Structural Health Monitoring (SHM) to ensure public safety and optimize maintenance schedules. Digital Twin technology, characterized b…
• Graph-driven digital twins as assistants to bridge maintenance
  2025 · 数字孪生 · (English) Bridges are vital components of transport infrastructure networks which are facing a widespread lack of resilience due to aging and changing environmental conditions. Finding more efficient methods for monitori…
• Topology analysis and evolution trend prediction of secure propagation networks for short videos based on digital twin model
  2025 · 数字孪生 · To address the problem of security analysis lag caused by the delay in dynamic topology updates in short video networks, this paper constructs a real-time digital twin framework based on edge computing lightweight proxie…
• Collaboration of IoT devices in smart home scenarios: algorithm research based on graph neural networks and federated learning
  2025 · 隐私计算与数据要素 · Traditional IoT device collaboration is usually static and cannot adjust the collaboration mode between devices according to various changes, which limits work efficiency. To this end, an IoT device collaboration optimiz…
• Auto-GNN: Neural architecture search of graph neural networks
  2022 · AI 安全与对齐 · Graph neural networks (GNNs) have been widely used in various graph analysis tasks. As the graph characteristics vary significantly in real-world systems, given a specific scenario, the architecture parameters need to be…
• Bearing Remaining Useful Life Prediction Based on Regression Shapalet and Graph Neural Network
  2022 · AI 安全与对齐 · Remaining useful life (RUL) prediction of bearing is essential to guarantee its safe operation. In recent years, deep learning (DL)-based methods attract a lot of research attention for accurate RUL prediction. However, …
• Interpretable Chirality-Aware Graph Neural Network for Quantitative Structure Activity Relationship Modeling in Drug Discovery
  2022 · AI 安全与对齐 · Abstract In computer-aided drug discovery, quantitative structure activity relation models are trained to predict biological activity from chemical structure. Despite the recent success of applying graph neural network t…
• Predicting stress, strain and deformation fields in materials and structures with graph neural networks
  2022 · AI 安全与对齐 · Developing accurate yet fast computational tools to simulate complex physical phenomena is a long-standing problem. Recent advances in machine learning have revolutionized the way simulations are approached, shifting fro…
• Deep hybrid: Multi-graph neural network collaboration for hyperspectral image classification
  2022 · AI 安全与对齐 · With limited number of labeled samples, hyperspectral image (HSI) classification is a difficult Problem in current research. The graph neural network (GNN) has emerged as an approach to semi-supervised classification, an…
• Graph Neural Networks in Network Neuroscience
  2022 · 脑科学 · Noninvasive medical neuroimaging has yielded many discoveries about the brain connectivity. Several substantial techniques mapping morphological, structural and functional brain connectivities were developed to create a …
• Self-Supervised Learning of Graph Neural Networks: A Unified Review
  2022 · 数字孪生 · Deep models trained in supervised mode have achieved remarkable success on a variety of tasks. When labeled samples are limited, self-supervised learning (SSL) is emerging as a new paradigm for making use of large amount…
• A Digital Twin of a Water Distribution System by Using Graph Convolutional Networks for Pump Speed-Based State Estimation
  2022 · 数字孪生 · Water distribution system monitoring is currently carried out using advanced real-time control technologies to achieve a higher operational efficiency. Data analysis techniques can be implemented for condition estimation…
• Think Global, Act Local: Dual-scale Graph Transformer for Vision-and-Language Navigation
  2022 · 具身智能 · Following language instructions to navigate in unseenaenvironments is a challenging problem for autonomous embodied agents. The agent not only needs to ground languages in visual scenes, but also should explore the envir…
• Graph neural networks for materials science and chemistry
  2022 · 量子材料 · Machine learning plays an increasingly important role in many areas of chemistry and materials science, being used to predict materials properties, accelerate simulations, design new structures, and predict synthesis rou…
• Spectral Temporal Graph Neural Network for Multivariate Time-series\n Forecasting
  2021 · AI 安全与对齐 · Multivariate time-series forecasting plays a crucial role in many real-world\napplications. It is a challenging problem as one needs to consider both\nintra-series temporal correlations and inter-series correlations\nsim…
• ATSE: a peptide toxicity predictor by exploiting structural and evolutionary information based on graph neural network and attention mechanism
  2021 · AI 安全与对齐 · MOTIVATION: Peptides have recently emerged as promising therapeutic agents against various diseases. For both research and safety regulation purposes, it is of high importance to develop computational methods to accurate…
• Learning How to Propagate Messages in Graph Neural Networks
  2021 · AI 安全与对齐 · This paper studies the problem of learning message propagation strategies for graph neural networks (GNNs). One of the challenges for graph neural networks is that of defining the propagation strategy. For instance, the …

以 API 获取该主题全量数据

# 主题词表（含本主题的站点分布与年度分布）
curl http://data.swarmlabs.tools/api/topics.json

# 主题共现知识图谱
curl http://data.swarmlabs.tools/api/graph.json

需要按主题批量拉取、导出 BibTeX 或接入 AI Agent？查看 数据下载与格式 或 MCP 接入。