Graph-Based Agentic AI with LangGraph: Workflow Pathways for Long-Running Stateful Business Processes
基于LangGraph的基于图的智能体人工智能:长期运行的有状态业务流程的工作流路径
Daniel Pearson, Sidney Shapiro, Emiliano Sebastian Gonzalez Venegas, Sanad Al-Khatib, Aurora Pinzón Arzola
机构
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Dhillon School of Business, University of Lethbridge(莱斯布里奇大学迪隆商学院)
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Universidad de Guadalajara(瓜达拉哈拉大学)
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Al Hussein Technical University(侯赛因技术大学)
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Universidad de Guanajuato(瓜纳华托大学)
Comments18 pages, 8 figures, 1 Table. Full research paper proposing a resilient two-stage orchestration framework for collaborative UAV-GBS deployment in mission-critical Air-Ground Integrated Networks (AGINs). This revised version introduces a game-theoretic approach (Egalitarian Bargaining Game) and an aerodynamic energy model to enhance system robustness. Under review at an IEEE journal
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Faculty of Science, Agriculture, and Engineering, Newcastle University Singapore(新加坡纽卡斯尔大学科学、农业与工程学院)
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School of Information and Control Engineering, Qingdao University of Technology(青岛理工大学信息与控制工程学院)
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Department of EEE, Amrita School of Engineering, Amrita Vishwa Vidyapeetham(阿姆瑞塔工程学院电气与电子工程系,阿姆瑞塔大学)
ATLAS: A Foundation Neural Sampler for Amorphous Materials
ATLAS:一种用于非晶材料的基础神经采样器
Mouyang Cheng, Denis Blessing, Botao Yu, Gerhard Neumann, Mingda Li, Carles Domingo-Enrich, Yuanqi Du
机构
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Microsoft Research New England(微软研究院新英格兰分部)
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Center for Computational Science and Engineering(计算科学与工程中心)
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MIT(麻省理工学院)
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Karlsruhe Institute of Technology(卡尔斯鲁厄理工学院)
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Department of Materials Science and Engineering(材料科学与工程系)
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Department of Computer Science and Engineering(计算机科学与工程系)
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OSU(俄亥俄州立大学)
Democratizing Advanced High-Throughput Imaging via Cross-Instrument Deep Learning-Enabled Modality Transfer
基于深度学习的独立显微镜模态转换用于高通量成像
Dominik Panek, Carina Rząca, Maksymilian Szczypior, Joanna Sorysz, Krzysztof Misztal, Zbigniew Baster, Zenon Rajfur
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Doctoral School of Exact and Natural Sciences, Jagiellonian University(雅盖隆大学精确与自然科学博士学院)
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Department of Molecular and Interfacial Biophysics, Faculty of Physics, Astronomy and Applied Computer Science, Jagiellonian University(物理、天文学与应用计算机科学学院分子与界面生物物理学系)
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Undergraduate program in Biophysics, Faculty of Physics, Astronomy and Applied Computer Science, Jagiellonian University(物理、天文学与应用计算机科学学院生物物理本科生项目)
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Undergraduate program in Biomedical Engineering, Faculty of Electrical Engineering, Automatics, Computer Science and Biomedical Engineering, AGH University of Science and Technology(AGH科技大学电气工程、自动化、计算机科学和生物医学工程学院生物医学工程本科生项目)
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Division of Computational Mathematics, Faculty of Mathematics and Computer Science, Jagiellonian University(雅盖隆大学数学与计算机科学学院计算数学系)
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Laboratory for Cell and Tissue Engineering, Department of Biomedical Engineering, Eindhoven University of Technology(埃因霍温理工大学生物医学工程系细胞与组织工程实验室)
Comments12 pages, 8 figures, accepted to IEEE QCE 2026 (QALG Track). Replaced the schematic in Fig. 8 with results based on real data and expanded the accompanying discussion
Real-time, inline quantitative MRI enabled by scanner-integrated machine learning: a proof of principle with NODDI
通过扫描仪集成的机器学习实现实时、在线定量MRI:NODDI的原理验证
Samuel Rot, Iulius Dragonu, Christina Triantafyllou, Matthew Grech-Sollars, Anastasia Papadaki, Laura Mancini, Stephen Wastling, Jennifer Steeden, John S. Thornton, Tarek Yousry, Claudia A. M. Gandini Wheeler-Kingshott, David L. Thomas, Daniel C. Alexander, Hui Zhang