„Graph Machine Learning“
Suchergebnisse
1.000+ Treffer
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Machine Learning Approaches in Cybersecurity to Enhance Security in Future Network Technologies
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Association rule learning for threat analysis using traffic analysis and packet filtering approach
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Load aware multipath data forwarding for enhanced lifetime of WSN
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Arabic sentiment analysis of Monkeypox using deep neural network and optimized hyperparameters of machine learning algorithms
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3D Successive Nanoscale Interactions‐Driven Mechanoreceptors with Broad Linear Range and Ultra‐High Sensitivity for Efficient Gesture Recognition (Adv. Funct. Mater. 34/2025)
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Cover Feature: Machine Learning Assisted for Preparation of Graphene Supported Cu‐Zn Catalyst for CO 2 Hydrogenation to Methanol (Chem. Asian J. 13/2025)
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GraphBNC: Machine Learning‐Aided Prediction of Interactions Between Metal Nanoclusters and Blood Proteins (Adv. Mater. 47/2024)
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Universal Ensemble‐Embedding Graph Neural Network for Direct Prediction of Optical Spectra from Crystal Structures (Adv. Mater. 46/2024)
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DSL4DPiFS – a graphical notation to model data pipeline deployment in forming systems
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Hate speech recognition in multilingual text: hinglish documents
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Extractive text summarization using deep learning approach
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Distributed Computing in Big Data Analytics – Concepts, Technologies and Applications
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Biomedical Engineering Systems and Technologies – 8th International Joint Conference, BIOSTEC 2015, Lisbon, Portugal, January 12-15, 2015, Revised Selected Papers
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Machine Learning Attacks‐Resistant Security by Mixed‐Assembled Layers‐Inserted Graphene Physically Unclonable Function (Adv. Sci. 30/2023)
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Intelligent Computing for Sustainable Development – First International Conference, ICICSD 2023, Hyderabad, India, August 25–26, 2023, Revised Selected Papers, Part II
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Accelerated First‐Principles Exploration of Structure and Reactivity in Graphene Oxide
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Accelerated First‐Principles Exploration of Structure and Reactivity in Graphene Oxide
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Combining expert knowledge and deep learning with case-based reasoning for predictive maintenance
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Accurate prediction of binding energies for two‐dimensional catalytic materials using machine learning
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Discovering rules for rule-based machine learning with the help of novelty search